• Biotech Sector

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    Breakthrough Using CRISPR to Target Fat Cells in Genetic Study of Obesity


    the boar


    Fat—it is vital for life but too much can lead to a host of health problems. Studying how fat tissue, or adipose, functions in the body is critical for understanding obesity and other issues.


    But structural differences in fat cells and their distribution throughout the body make doing so challenging.


    “Fat cells are different from other cells in that they lack unique cell surface receptors and only account for a minority of the cells within fat tissue,” said Steven Romanelli, Ph.D., from the Department of Molecular & Integrative Physiology at the University of Michigan.


    In a new paper published in the Journal of Biological Chemistry, Romanelli, Ormand MacDougald, Ph.D. and their colleagues describe a breakthrough using CRISPR-Cas9, a tool that has transformed molecular biological research, but whose use in the study of adipose tissue had been elusive.


    It’s a gene editing technique comprised of an enzyme called Cas9, which can break strands of DNA, and a piece of RNA that guides the Cas9 enzyme to a specific site in the genome for editing. The tool has been successfully used to study heart, liver, neurons, and skin cells, to name a few, but never a certain type of adipose cells known as brown fat.

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    Aglobal effort to map the genomes of all plants, animals, fungi and other eukaryotic life on Earth is entering a new phase as it moves from pilot projects to full-scale production sequencing. This new phase of The Earth BioGenome Project, or EBP, is marked with a collection of papers published this week (Jan. 17) in Proceedings of the National Academy of Sciences, describing the project’s goals, achievements to date and next steps.


    “The special feature on the EBP captures the essence and excitement of the largest-scale coordinated effort in the history of biology,” said Harris Lewin, chair of the EBP Working Group and Distinguished Professor of evolution and ecology at the University of California, Davis. “From fundamental science to breakthrough applications across a wide range of pressing global problems, such as preventing biodiversity loss and adapting food crops to climate change, the EBP’s progress in sequencing eukaryotic life is humbling and inspiring. Achieving the ultimate goal of sequencing all eukaryotic life now seems within our reach.”


    Launched in November 2018, the goal of the EBP is to provide a complete DNA sequence catalog of all 1.8 million named species of plants, animals and fungi as well as single-celled eukaryotes.



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    It’s a bit difficult to pin down exactly what people in the biotechnology industry mean by “artificial intelligence” (AI). In general, they seem content with a working definition, one that describes AI as a computer program that can learn and predict outcomes based on the data sets it receives.


    Given that the working definition of AI is vague, it follows that the status of AI in the biotechnology industry is vague, too. For example, it is unclear whether AI is to be regarded as something new and revolutionary. Are news stories in the popular press any guide? These include breathless reports of how AlphaFold, an AI system developed by Google’s DeepMind, accurately predicted the structure of hundreds of thousands of proteins.


    Although AlphaFold is a groundbreaking technology, it isn’t the be-all and end-all of AI in biotechnology. AI-related spadework in biotechnology is occuring in several fields of endeavor. Indeed, biotechnology companies far and wide have been implementing AI in their pipelines.


    If we are to clarify AI’s status, we should begin by recognizing that AI in biotechnology hasn’t suddenly become mainstream. In fact, it is already mainstream. Moreover, it is diverse and ready to produce results. In the biotechnology industry, AI that is accurate, predictive, and productive is within reach. Such AI will be worth a hundred times its weight in bench lab scientists.


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    Tailor-Made Medicine? How Precision Medicine Can Improve With Data


    PR Newswire


    Access to data, including genetic data, can make precision medicine more feasible and cost-effective. And, fortunately, the methods for finding, aggregating, comparing and analyzing data are improving by the day.


    Better tools — including those that utilize artificial intelligence (AI) and machine learning — are being developed and fine-tuned to enable doctors to make decisions about a patient’s individualized treatment. These AI tools are also becoming more readily available. The widespread ability for medical teams to work with data in this way is going to make precision medicine a reality for increasingly more people.


    To keep the momentum going in the continued development of precision medicine, it’s vital to demonstrate that it’s really working. Imaging can be one important component to achieving that end goal.


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    X Marks the $100 Genome: Illumina Presents New Chemistry, Strong Results




    At J.P. Morgan conference, Illumina shares new sequencing-by-synthesis chemistry and gears up for its long-read Infinity launch later this year, plus numerous collaborations and numbers that beat Wall Street expectations.


    Illumina CEO Francis deSouza disclosed that his company has developed a new sequencing-by-synthesis (SBS) chemistry—codenamed “Chemistry X” pending a permanent name.


    He said Chemistry X will deliver 2x faster cycle times, as well as 2x longer reads, and 3x greater accuracy than the company’s current SBS chemistry. Additional details of Chemistry X are expected to emerge this fall, when Illumina holds its annual customer/investor day.

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    Can genetically engineered seeds prevent a climate-driven food crisis?


    Yale Climate Coonections


    Most researchers agree that increasing the diversity in varieties and in the kinds of crops that are grown is an essential part of reducing crop loss risk.


    Publicly funded research could help and could bring enormous benefit to society, some say. One study found that for every one dollar of taxpayer money invested into agricultural research and development, $10 in benefits were returned to society.


    Such a move would require a turnaround: Public universities have traditionally been a major source of plant breeding research, but federal funding has fallen since the mid-20th century.


    New technologies may also allow for new seed varieties to be created more quickly and at a lower cost. For example, seed modified using CRISPR – a technology that allows scientists to “edit” existing DNA without introducing genetic material from another organism like in genetic engineering – doesn’t face the same regulations as genetically engineered seed. As a result, CRISPR-created seed may move into the field more quickly and affordably.