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News Article | May 25, 2017
Site: www.eurekalert.org

Around 1% of patients with HIV - known as elite controllers - are able to survive without antiviral treatment, because their immune systems produce certain kinds of HIV-specific antibodies: proteins that recognise features on the surface of the virus and bind to them, making the virus inactive. The challenge in developing an HIV vaccine is to identify specific features in the proteins on the virus's surface which are recognised by the immune system and elicit a response similar to that seen in elite controllers. A widely used technique for studying proteins on the surfaces of cells - which is sometimes also used with viruses - is fluorescence-activated cell sorting (FACS). You take a sample of cells and add fluorescent antibodies that bind to the surface proteins you're interested in. Cells with proteins that are recognised by the antibodies will become fluorescent, while cells lacking such proteins will not. You can then measure the fluorescence of each cell individually, sending the fluorescent cells into one container for further study, and the non-fluorescent cells into another. This works well for studying cells, which have hundreds of surface proteins for the antibodies to bind to, producing a strong fluorescence signal. FACS can also be used to sort large viruses such as the Ebola virus, but for studying smaller viruses with fewer surface proteins - like HIV - FACS is not sensitive enough. Now researchers at EMBL, ESPCI Paris, and the International AIDS Vaccine Initiative have developed a new technique for rapidly sorting HIV viruses, which could lead to more rapid development of a vaccine for HIV, as they report in Cell Chemical Biology. Study author Christoph Merten explains. What did you do? We developed a system that enables us to analyse and sort HIV at a rate of hundreds of viruses per second, separating the viruses according to whether or not their surface proteins have features recognised by specific antibodies. Instead of using fluorescent antibodies that would bind directly to the viral proteins - producing only a weak signal - we took the ordinary, non-fluorescent antibodies and attached them to an enzyme called alkaline phosphatase (AP). We then enclosed the viruses individually in droplets of liquid, along with a chemical that becomes fluorescent when acted on by AP. The antibodies bind to the viral proteins, and the attached AP enzymes produce many fluorescent molecules which remain inside the liquid droplet, creating a strong fluorescence signal. If the virus's proteins don't have the right features, the antibodies with their AP enzymes will not bind and no fluorescence is produced. We can therefore study individual viruses, sorting them with high accuracy according to whether they show features that could be exploited in developing a vaccine against HIV. Ours is a microfluidic system - in other words, it uses technology designed for manipulating extremely small quantities of liquid. The whole system is contained on a microfluidic 'chip' - a palm-sized device consisting of microscopic networks of channels for liquid to flow through. These channels are just a few hundredths of a millimetre across, and each droplet in our experiments is around 30 billionths of a millilitre. Microfluidic chips offer particular advantages when working with pathogens like HIV, since they're completely sealed and therefore very safe to use. Typical FACS systems can produce airborne droplets, so much more stringent containment measures are required when working with harmful bacteria and viruses. Why does it matter? Our method makes it possible to analyse and sort HIV viruses in quantities and at speeds that have not been possible before. This enables us to rapidly test millions of viral variants, which should significantly speed up the process of vaccine development. In our experiments each droplet contained a virus and antibodies, but it should also be possible to add a cell to the droplet and study whether the antibodies can stop the virus from entering the cell. That's not possible with FACS, so it opens up many possibilities for future research.


Researchers at EMBL, ESPCI Paris, and the International AIDS Vaccine Initiative have developed a new technique for rapidly sorting HIV viruses, which could lead to more rapid development of a vaccine for HIV, as they report in Cell Chemical Biology. The technique will enable scientists to identify specific features in the proteins on the virus's surface which are recognized by the immune system and elicit a response similar to that seen in elite controllers -- patients that are able to survive without antiviral treatment. Around 1% of patients with HIV -- known as elite controllers -- are able to survive without antiviral treatment, because their immune systems produce certain kinds of HIV-specific antibodies: proteins that recognise features on the surface of the virus and bind to them, making the virus inactive. The challenge in developing an HIV vaccine is to identify specific features in the proteins on the virus's surface which are recognized by the immune system and elicit a response similar to that seen in elite controllers. A widely used technique for studying proteins on the surfaces of cells -- which is sometimes also used with viruses -- is fluorescence-activated cell sorting (FACS). You take a sample of cells and add fluorescent antibodies that bind to the surface proteins you're interested in. Cells with proteins that are recognized by the antibodies will become fluorescent, while cells lacking such proteins will not. You can then measure the fluorescence of each cell individually, sending the fluorescent cells into one container for further study, and the non-fluorescent cells into another. This works well for studying cells, which have hundreds of surface proteins for the antibodies to bind to, producing a strong fluorescence signal. FACS can also be used to sort large viruses such as the Ebola virus, but for studying smaller viruses with fewer surface proteins -- like HIV -- FACS is not sensitive enough. Now researchers at EMBL, ESPCI Paris, and the International AIDS Vaccine Initiative have developed a new technique for rapidly sorting HIV viruses, which could lead to more rapid development of a vaccine for HIV, as they report in Cell Chemical Biology. Study author Christoph Merten explains. What did you do? We developed a system that enables us to analyse and sort HIV at a rate of hundreds of viruses per second, separating the viruses according to whether or not their surface proteins have features recognized by specific antibodies. Instead of using fluorescent antibodies that would bind directly to the viral proteins -- producing only a weak signal -- we took the ordinary, non-fluorescent antibodies and attached them to an enzyme called alkaline phosphatase (AP). We then enclosed the viruses individually in droplets of liquid, along with a chemical that becomes fluorescent when acted on by AP. The antibodies bind to the viral proteins, and the attached AP enzymes produce many fluorescent molecules which remain inside the liquid droplet, creating a strong fluorescence signal. If the virus's proteins don't have the right features, the antibodies with their AP enzymes will not bind and no fluorescence is produced. We can therefore study individual viruses, sorting them with high accuracy according to whether they show features that could be exploited in developing a vaccine against HIV. Ours is a microfluidic system -- in other words, it uses technology designed for manipulating extremely small quantities of liquid. The whole system is contained on a microfluidic 'chip' -- a palm-sized device consisting of microscopic networks of channels for liquid to flow through. These channels are just a few hundredths of a millimetre across, and each droplet in our experiments is around 30 billionths of a millilitre. Microfluidic chips offer particular advantages when working with pathogens like HIV, since they're completely sealed and therefore very safe to use. Typical FACS systems can produce airborne droplets, so much more stringent containment measures are required when working with harmful bacteria and viruses. Why does it matter? Our method makes it possible to analyse and sort HIV viruses in quantities and at speeds that have not been possible before. This enables us to rapidly test millions of viral variants, which should significantly speed up the process of vaccine development. In our experiments each droplet contained a virus and antibodies, but it should also be possible to add a cell to the droplet and study whether the antibodies can stop the virus from entering the cell. That's not possible with FACS, so it opens up many possibilities for future research.


News Article | May 25, 2017
Site: www.scientificcomputing.com

The Broad Institute of MIT and Harvard will release version 4 of the industry-leading Genome Analysis Toolkit under an open source software license. The software package, designated GATK4, contains new tools and rebuilt architecture. It is available currently as an alpha preview on the Broad Institute’s GATK website, with a beta release expected in mid-June. Broad engineers announced the upgrade, as well as the decision to release the tool as an open source product, at Bio-IT World today. The new version is built on a new architecture, allowing significant streamlining of individual tools and support for performance-enhancing technologies such as Apache Spark. This new framework brings improvements to parallelization, capitalizing on cloud deployment and making the process of analyzing vast amounts of genomic data easier, faster, and more efficient. “We wanted to remove traditional barriers of scale while offering the same high level of data quality our users expect,” said Eric Banks, Senior Director of Data Sciences and Data Engineering at Broad and a creator of the original GATK software package. “Thanks to the rapid adoption of cloud computing, researchers can finally do away with many of the infrastructure-related complications that have hampered progress, especially at smaller institutions and startups.” Today, more than 45,000 academic and commercial users worldwide rely on the GATK, running millions of analyses. The GATK is the industry standard for identifying SNPs and indels in germline DNA and RNAseq data. In addition to improving the performance of these established tools, GATK4 extends this scope of analysis to include copy number and structural variation, for both germline and somatic research applications. GATK4 will be released as a fully open source product, thanks in part to a collaboration between Broad Institute and Intel Corporation to advance high-performance analytics so researchers can study massive amounts of genomic data from diverse sources worldwide. At the Intel-Broad Center for Genomic Data Engineering, software engineers and researchers have spent the last several months building, optimizing, and widely sharing new tools and infrastructure to help scientists integrate and process genomic data. GATK4 has benefited from this collaboration, which has helped engineers optimize best practices in hardware and software for genome analytics to make it possible to combine and use research data sets that reside on private, public, and hybrid clouds. “Releasing GATK4 as open source was the obvious next step for our team,” said Geraldine Van der Auwera, Associate Director of Outreach and Communications within the Data Science and Data Engineering group at the Broad Institute. “We believe it’s the most effective way to support the community, and we hope it continues to grow, innovate, and help researchers make insights that are essential for future human health breakthroughs.” “It is critical for progress in biomedicine that the software we use for analysing the genomes of millions of people is robust and well understood,” said Ewan Birney, Director of EMBL-EBI and Chair of the Global Alliance for Genomics and Health (GA4GH). “Releasing GATK software with an open source license directly supports open innovation, data re-use and data re-analysis in the global biomedical community.” “The GATK tools are crucial for both germline and cancer analyses,” said Robert L. Grossman of the University of Chicago Department of Medicine and an expert in biomedical informatics. “Releasing GATK4 as an open source software package will increase adoption, and benefit the community.” “Open sourcing the GATK is a big deal for open genomics, and for open science in general,” said Jeremy Freeman, manager of computational biology at the Chan Zuckerberg Initiative (CZI). “Not only does it make this critical tool available to as broad as possible an audience for use, reuse, inspection, and contribution -- it provides a powerful example to the community for how an existing project can embrace open source.” “Open source code is a foundation of efficient biomedical research,” said Brad Chapman, a research scientist at the Harvard T.H. Chan School of Public Health. “It enables reproducibility, reuse and remixing by removing barriers for sharing and distributing analyses. The Broad Institute’s GATK team leads in the development of scalable, sensitive and specific variant calling algorithms, and open sourcing GATK4 will allow frameworks like Blue Collar Bioinformatics to make these methods broadly available to the scientific research community.” “Cloudera has always been a supporter and believer in the power of open source code,” said Tom White, data scientist at Cloudera and a member of the Apache Hadoop PMC. “We’ve been excited to contribute to the GATK codebase, to make it run smoothly on Apache Spark™ and Cloudera. This next phase of the GATK, powered by Spark and open source software, will expand access and improve collaboration among genomic data scientists.” “The open sourcing of GATK4 is a great step for genomics, allowing for scalability and performance gains to be openly available to the research, biotech and pharmaceutical communities,” said Jason Waxman, corporate vice president and general manager of Data Center Solutions at Intel. “GATK4, when run on Intel’s new reference architecture, can achieve a 5X speed-up compared to earlier versions of the software.” “We at Google are excited to see this new release,” said Ilia Tulchinsky, Google Cloud Healthcare Engineering Lead. “We’ve been collaborating with the Broad Institute for the past three years to enhance genomic processing on Google Cloud Platform. As a strong supporter for open source technology, we believe that making GATK available this way will facilitate its use by genomic scientists everywhere. As fellow collaborators with Intel, we particularly look forward to enabling researchers to run GATK4 on Google Cloud using the upcoming Intel Xeon processor Scalable family.” “The GATK is one of the most widely-utilized software packages in the life sciences, and our team has worked very productively with Broad to accelerate it for use on Azure,” said Geralyn Miller, Director, AI & Research, Microsoft. “This new model will greatly facilitate this effort going forward, and we are excited to continue and expand our efforts around GATK on Azure.” “With the open source launch of GATK4, there is an opportunity to create a global community that can collaborate together and advance the state of art in bioinformatics,” said Hong Tang, chief architect at Alibaba Cloud, the cloud computing arm of Alibaba Group. “We look forward to closely working with Broad Institute in bringing the cloud-based GATK service to genomics customers in China, as well as in ongoing GATK research and development.” In addition to offering GATK4 as an open source toolkit, Broad Institute will continue to offer user support, training, and outreach on its popular user support forum. GATK4, like many of the Broad Institute’s genome analysis tools, will be available through the Broad Institute’s cloud based analysis platform, FireCloud.


"We wanted to remove traditional barriers of scale while offering the same high level of data quality our users expect," said Eric Banks, Senior Director of Data Sciences and Data Engineering at Broad and a creator of the original GATK software package. "Thanks to the rapid adoption of cloud computing, researchers can finally do away with many of the infrastructure-related complications that have hampered progress, especially at smaller institutions and startups." Today, more than 45,000 academic and commercial users worldwide rely on the GATK, running millions of analyses. The GATK is the industry standard for identifying SNPs and indels in germline DNA and RNAseq data. In addition to improving the performance of these established tools, GATK4 extends this scope of analysis to include copy number and structural variation, for both germline and somatic research applications. GATK4 will be released as a fully open source product, thanks in part to a collaboration between Broad Institute and Intel Corporation to advance high-performance analytics so researchers can study massive amounts of genomic data from diverse sources worldwide. At the Intel-Broad Center for Genomic Data Engineering, software engineers and researchers have spent the last several months building, optimizing, and widely sharing new tools and infrastructure to help scientists integrate and process genomic data. GATK4 has benefited from this collaboration, which has helped engineers optimize best practices in hardware and software for genome analytics to make it possible to combine and use research data sets that reside on private, public, and hybrid clouds. "Releasing GATK4 as open source was the obvious next step for our team," said Geraldine Van der Auwera, Associate Director of Outreach and Communications within the Data Science and Data Engineering group at the Broad Institute. "We believe it's the most effective way to support the community, and we hope it continues to grow, innovate, and help researchers make insights that are essential for future human health breakthroughs." "It is critical for progress in biomedicine that the software we use for analysing the genomes of millions of people is robust and well understood," said Ewan Birney, Director of EMBL-EBI and Chair of the Global Alliance for Genomics and Health (GA4GH). "Releasing GATK software with an open source license directly supports open innovation, data re-use and data re-analysis in the global biomedical community." "The GATK tools are crucial for both germline and cancer analyses," said Robert L. Grossman of the University of Chicago Department of Medicine and an expert in biomedical informatics. "Releasing GATK4 as an open source software package will increase adoption, and benefit the community." "Open sourcing the GATK is a big deal for open genomics, and for open science in general," said Jeremy Freeman, manager of computational biology at the Chan Zuckerberg Initiative (CZI). "Not only does it make this critical tool available to as broad as possible an audience for use, reuse, inspection, and contribution -- it provides a powerful example to the community for how an existing project can embrace open source." "Open source code is a foundation of efficient biomedical research," said Brad Chapman, a research scientist at the Harvard T.H. Chan School of Public Health. "It enables reproducibility, reuse and remixing by removing barriers for sharing and distributing analyses. The Broad Institute's GATK team leads in the development of scalable, sensitive and specific variant calling algorithms, and open sourcing GATK4 will allow frameworks like Blue Collar Bioinformatics to make these methods broadly available to the scientific research community." "Cloudera has always been a supporter and believer in the power of open source code," said Tom White, data scientist at Cloudera and a member of the Apache Hadoop PMC. "We've been excited to contribute to the GATK codebase, to make it run smoothly on Apache Spark™ and Cloudera. This next phase of the GATK, powered by Spark and open source software, will expand access and improve collaboration among genomic data scientists." "The open sourcing of GATK4 is a great step for genomics, allowing for scalability and performance gains to be openly available to the research, biotech and pharmaceutical communities," said Jason Waxman, corporate vice president and general manager of Data Center Solutions at Intel. "GATK4, when run on Intel's new reference architecture, can achieve a 5X speed-up compared to earlier versions of the software." "We at Google are excited to see this new release," said Ilia Tulchinsky, Google Cloud Healthcare Engineering Lead. "We've been collaborating with the Broad Institute for the past three years to enhance genomic processing on Google Cloud Platform. As a strong supporter for open source technology, we believe that making GATK available this way will facilitate its use by genomic scientists everywhere. As fellow collaborators with Intel, we particularly look forward to enabling researchers to run GATK4 on Google Cloud using the upcoming Intel Xeon processor Scalable family." "The GATK is one of the most widely-utilized software packages in the life sciences, and our team has worked very productively with Broad to accelerate it for use on Azure," said Geralyn Miller, Director, AI & Research, Microsoft. "This new model will greatly facilitate this effort going forward, and we are excited to continue and expand our efforts around GATK on Azure." "With the open source launch of GATK4, there is an opportunity to create a global community that can collaborate together and advance the state of art in bioinformatics," said Hong Tang, chief architect at Alibaba Cloud, the cloud computing arm of Alibaba Group. "We look forward to closely working with Broad Institute in bringing the cloud-based GATK service to genomics customers in China, as well as in ongoing GATK research and development." In addition to offering GATK4 as an open source toolkit, Broad Institute will continue to offer user support, training, and outreach on its popular user support forum. GATK4, like many of the Broad Institute's genome analysis tools, will be available through the Broad Institute's cloud based analysis platform, FireCloud. About the Broad Institute of MIT and Harvard Broad Institute of MIT and Harvard was launched in 2004 to empower this generation of creative scientists to transform medicine. The Broad Institute seeks to describe all the molecular components of life and their connections; discover the molecular basis of major human diseases; develop effective new approaches to diagnostics and therapeutics; and disseminate discoveries, tools, methods, and data openly to the entire scientific community. Founded by MIT, Harvard, Harvard-affiliated hospitals, and the visionary Los Angeles philanthropists Eli and Edythe L. Broad, the Broad Institute includes faculty, professional staff, and students from throughout the MIT and Harvard biomedical research communities and beyond, with collaborations spanning over a hundred private and public institutions in more than 40 countries worldwide. For further information about the Broad Institute, go to http://www.broadinstitute.org. To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/broad-institute-to-release-genome-analysis-toolkit-4-gatk4-as-open-source-resource-to-accelerate-research-300463193.html


News Article | May 10, 2017
Site: www.eurekalert.org

Reported in Nature today, one of the largest sets of high quality human induced pluripotent stem cell lines from healthy individuals has been produced by a consortium involving the Wellcome Trust Sanger Institute. Comprehensively annotated and available for independent research*, the hundreds of stem cell lines are a powerful resource for scientists studying human development and disease. With collaborative partners from King's College London, the European Bioinformatics Institute, the University of Dundee and the University of Cambridge, the study also investigates in unprecedented detail the extensive variation between stem cells from different healthy people. Technological advancements have made it possible to take an adult cell and use specific growth conditions to turn back the clock - returning it to an early embryonic state. This results in an induced pluripotent stem cell (iPSC), which can develop into any type of cell in the body. These iPSCs have huge scientific potential for studying the development and the impact of diseases including cancer, Alzheimer's, and heart disease. However, the process of creating an iPSC is long and complicated and few laboratories have the facilities to characterise their cells in a way that makes them useful for other scientists to use. The Human Induced Pluripotent Stem Cell Initiative (HipSci) project used standardised methods to generate iPSCs on a large scale to study the differences between healthy people. Reference sets of stem cells were generated from skin biopsies donated by 301 healthy volunteers, creating multiple stem cell lines from each person. The researchers created 711 cell lines and generated detailed information about their genome, the proteins expressed in them, and the cell biology of each cell line. Lines and data generated by this initiative are available to academic researchers and industry. Dr Daniel Gaffney, a lead author on the paper, from the Wellcome Trust Sanger Institute, said: "We have created a comprehensive, high quality reference set of human induced pluripotent stem cell lines from healthy volunteers. Each of these stem cell lines has been extensively characterised and made available to the wider research community along with the annotation data. This resource is a stepping stone for researchers to make better cell models of many diseases, because they can study disease risk in many cell types, including those that are normally inaccessible." By creating more than one stem cell line from each healthy individual, the researchers were able to determine the similarity of stem cell lines from the same person. Prof Fiona Watt, a lead author on the paper and co-principal investigator of HipSci, from King's College London, said: "Many other efforts to create stem cells focus on rare diseases. In our study, stem cells have been produced from hundreds of healthy volunteers to study common genetic variation. We were able to show similar characteristics of iPS cells from the same person, and revealed that up to 46 per cent of the differences we saw in iPS cells were due to differences between individuals. These data will allow researchers to put disease variations in context with healthy people." The project, which has taken 4 years to complete, required a multidisciplinary approach with many different collaborators, who specialised in different aspects of creating the cell lines and characterising the data. Dr Oliver Stegle, a lead author on the paper, from the European Bioinformatics Institute, said: "This study was only possible due to the large scale, systematic production and characterisation of the stem cell lines. To help us to understand the different properties of the cells, we collected extensive data on multiple molecular layers, from the genome of the lines to their cell biology. This type of phenotyping required a whole facility rather than just a single lab, and will provide a huge resource to other scientists. Already, the data being generated have helped to gain a clearer picture of what a typical human iPSC cell looks like." Dr Michael Dunn, Head of Genetics and Molecular Sciences at Wellcome, said: "This is the fantastic result of many years of work to create a national resource of high quality, well-characterised human induced pluripotent stem cells. This has been a significant achievement made possible by the collaboration of researchers across the country with joint funding provided by Wellcome and the MRC. It will help to provide the knowledge base to underpin a huge amount of future research into the effects of our genes on health and disease. By ensuring this resource is openly available to all, we hope that it will pave the way for many more fascinating discoveries." *Data and cell lines from this study are being made available through http://www. , the European Collection of Authenticated Cell Cultures (ECACC) and the European Bank for Induced Pluripotent Stem Cells (EBiSC). Hipsci brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a global induced pluripotent stem cell resource for the research community. http://www. King's College London is one of the top 25 universities in the world (2016/17 QS World University Rankings) and among the oldest in England. King's has more than 29,600 students (of whom nearly 11,700 are graduate students) from some 150 countries worldwide, and some 8,000 staff. King's has an outstanding reputation for world-class teaching and cutting-edge research. In the 2014 Research Excellence Framework (REF), eighty-four per cent of research at King's was deemed 'world-leading' or 'internationally excellent' (3* and 4*). Since our foundation, King's students and staff have dedicated themselves in the service of society. King's will continue to focus on world-leading education, research and service, and will have an increasingly proactive role to play in a more interconnected, complex world. Visit our website to find out more about Vision 2029, King's strategic vision for the next 12 years to 2029, which will be the 200th anniversary of the founding of the university. http://www. The European Bioinformatics Institute (EMBL-EBI) is a global leader in the storage, analysis and dissemination of large biological datasets. EMBL-EBI helps scientists realise the potential of 'big data' by enhancing their ability to exploit complex information to make discoveries that benefit humankind. EMBL-EBI is at the forefront of computational biology research, with work spanning sequence analysis methods, multi-dimensional statistical analysis and data-driven biological discovery, from plant biology to mammalian development and disease. We are part of the European Molecular Biology Laboratory (EMBL), an international, innovative and interdisciplinary research organisation funded by 22 member states and two associate member states, and are located on the Wellcome Genome Campus, one of the world's largest concentrations of scientific and technical expertise in genomics. http://www. The Wellcome Trust Sanger Institute is one of the world's leading genome centres. Through its ability to conduct research at scale, it is able to engage in bold and long-term exploratory projects that are designed to influence and empower medical science globally. Institute research findings, generated through its own research programmes and through its leading role in international consortia, are being used to develop new diagnostics and treatments for human disease. http://www. Wellcome exists to improve health for everyone by helping great ideas to thrive. We're a global charitable foundation, both politically and financially independent. We support scientists and researchers, take on big problems, fuel imaginations and spark debate. http://www.


Letunic I.,Biobyte Solutions GmbH | Doerks T.,EMBL | Bork P.,EMBL
Nucleic Acids Research | Year: 2015

SMART (Simple Modular Architecture Research Tool) is a web resource (http://smart.embl.de/) providing simple identification and extensive annotation of protein domains and the exploration of protein domain architectures. In the current version, SMART contains manually curated models for more than 1200 protein domains, with ∼200 new models since our last update article. The underlying protein databases were synchronized with UniProt, Ensembl and STRING, bringing the total number of annotated domains and other protein features above 100 million. SMART's 'Genomic' mode, which annotates proteins from completely sequenced genomes was greatly expanded and now includes 2031 species, compared to 1133 in the previous release. SMART analysis results pages have been completely redesigned and include links to several new information sources. A new, vector-based display engine has been developed for protein schematics in SMART, which can also be exported as highresolution bitmap images for easy inclusion into other documents. Taxonomic tree displays in SMART have been significantly improved, and can be easily navigated using the integrated search engine. © The Author(s) 2014.


Maitre J.-L.,EMBL | Heisenberg C.-P.,IST Austria
Current Biology | Year: 2013

Cadherins are transmembrane proteins that mediate cell-cell adhesion in animals. By regulating contact formation and stability, cadherins play a crucial role in tissue morphogenesis and homeostasis. Here, we review the three major functions of cadherins in cell-cell contact formation and stability. Two of those functions lead to a decrease in interfacial tension at the forming cell-cell contact, thereby promoting contact expansion - first, by providing adhesion tension that lowers interfacial tension at the cell-cell contact, and second, by signaling to the actomyosin cytoskeleton in order to reduce cortex tension and thus interfacial tension at the contact. The third function of cadherins in cell-cell contact formation is to stabilize the contact by resisting mechanical forces that pull on the contact. © 2013 Elsevier Ltd.


Letunic I.,EMBL | Doerks T.,EMBL | Bork P.,EMBL
Nucleic Acids Research | Year: 2012

SMART (Simple Modular Architecture Research Tool) is an online resource (http://smart.embl.de/) for the identification and annotation of protein domains and the analysis of protein domain architectures. SMART version 7 contains manually curated models for 1009 protein domains, 200 more than in the previous version. The current release introduces several novel features and a streamlined user interface resulting in a faster and more comfortable workflow. The underlying protein databases were greatly expanded, resulting in a 2-fold increase in number of annotated domains and features. The database of completely sequenced genomes now includes 1133 species, compared to 630 in the previous release. Domain architecture analysis results can now be exported and visualized through the iTOL phylogenetic tree viewer. 'metaSMART' was introduced as a novel subresource dedicated to the exploration and analysis of domain architectures in various metagenomics data sets. An advanced full text search engine was implemented, covering the complete annotations for SMART and Pfam domains, as well as the complete set of protein descriptions, allowing users to quickly find relevant information. © The Author(s) 2011. Published by Oxford University Press.

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