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June 15, 2017 (Vol. 37, No. 12)

Synthetic Biology Expands and Grows

Rapidly Developing Field Is an Amalgam of Genetics, Automation, and Computer Algorithms

  • Virtual Cloud Lab

    Transcriptic provides access to an on-demand, automated lab in the cloud, obviating the need for laboratory automation, equipment, or even laboratory space itself.

    “Moving liquids around by human hands, with or without automation, is the way of the past,” says Yvonne Linney, Ph.D., CEO, Transcriptic.

    “Our fully automated lab is available virtually at any time, day or night via our web app. We accelerate knowledge and speed up discovery by providing a seamless connection between experimental design and data. The design of each subsequent experiment is supported by the data from the previous experiment, all within a unified software interface.”

    Transcriptic’s robotic cloud lab is a deeply integrated technology stack of biology, robotics, and software made available to its users via the internet. Transcriptic translates a user’s protocol into an open-data standard called Autoprotocol. Predesigned protocols covering a range of typical lab experiments are also available.

    Once a Transcriptic user submits an experiment, the robotic cloud lab dynamically provisions enough robotic capability and reagents to complete the experiment at whatever its scale. The underlying robotic infrastructure is a series of Workcells, the size of a shipping containers, filled with fully integrated laboratory equipment. The Workcells form a single virtual lab connected by software all with a single interface to the user. Each Workcell can be programmed separately, and operated remotely.

    In a proof-of-concept project (collaboration with Synthego, Transcriptic devised an automated, scalable solution to capture the entire workflow for CRISPR/Cas9-mediated editing, from the synthesis of single-guide RNAs to validation by sequencing of edited mammalian cells. It took less than three weeks to convert the Synthego protocol to Autoprotocol for Transcriptic’s cloud lab.

    A collaboration with EpiBiome yielded an automated, high-throughput, and reproducible microbial sample preparation and Ribosomal 16S sequencing pipeline, entirely completed in 7–10 days. Such a rapid and highly scalable protocol offers an opportunity for large-scale microbiome profiling and identification of disease-associated bacteria. “The scientific community struggles with data reproducibility at different locations,” commented Dr. Linney. “In the future, Transcriptic will be able to connect any lab to our cloud, increasing data consistency and transparency.”

  • Gene Optimization

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    Open reading frames (ORFs) of three intracellular proteins and two antibodies were optimized with Thermo Fisher Scientific’s GeneOptimizer algorithm. Subsequently, protein expression was compared to wild-type counterparts, which was normalized to a value of 1.

    “Scientists should focus on idea generation, experimental design, and data analysis. We take on the grunt work of synthetic biology: gene synthesis, cloning, and expression,” echoes Axel Trefzer, Ph.D., R&D leader, Thermo Fisher Scientific, adding that GeneArt™ gene synthesis products and services allow for easy design of artificial sequences and their seamless adaptation to a desired host. Users can combine features of different organisms and optimize function without affecting protein function, and thus produce meaningful DNA sequences.

    GeneArt gene synthesis supports design of gene sequences of the highest complexity in a range of sizes up to 100 kb. Conversely, GeneArt Strings™ DNA fragments are uncloned DNA fragments up to 3,000 bp in length, assembled from synthetic oligonucleotides.

    “Optimization of gene sequences is a key for producing functional DNA in a target organism,” continues Dr. Trefzer. “GeneArt GeneOptimizer™ aims to solve traditional protein expression limitations, such as low yields and unstable, transient expression.”

    Using data available from published literature in combination with proprietary data, the GeneOptimizer algorithm determines the optimal gene sequence for a given expression experiment. The company emphasizes high reliability of the design algorithms. The Thermo Fisher Cloud suite of apps interactively guides customers through the design process, highlights problematic areas and enables sequentially optimization until an optimal result is realized. Optimization of genes and DNA fragments have been experimentally proven to increase protein expression rates up to 100-fold in a variety of host systems.

    For example, Mapp Biopharmaceutical was able to optimize expression of several monoclonal antibodies, all part of Ebola ZMapp™ therapy. GeneArt Gene Synthesis was also recently utilized in a high-profile application to generate a first-time Zika virus diagnostic assay.

    The real-time PCR-based Versant® Zika RNA 1.0 Assay (kPCR) developed by
    Siemens Healthineers amplifies and detects all currently identified Zika genotypes, including Asian and African clusters.

    “We continue increasing our suite of ‘design-build-test’ apps for scientists” says Oliver Gathmann, manager of bioinformatics, Thermo Fisher Scientific. “This, in combination with our wide set of synthetic biology tools, including DNA libraries, directed evolution, and protein purification services, enable them to execute their vision with shortened timelines and increased reproducibility.

  • Diagnosing Alzheimer’s Using Saliva Biomarkers

    Investigators at the Beaumont Research Institute, part of Beaumont Health in Michigan, believe they have discovered small molecules in saliva that will help identify those at risk of developing Alzheimer’s disease. The results of this new study were published recently in the Journal of Alzheimer’s Disease in an article entitled “Diagnostic Biomarkers of Alzheimer’s Disease as Identified in Saliva using 1H NMR-Based Metabolomics.”

    Alzheimer’s currently has no cure, few reliable diagnostic tests, and is predicted to reach epidemic proportions worldwide by 2050. As a result, scientists are scrambling to develop methods that can quickly and accurately diagnose the neurodegenerative disorder. In the new study, the Beaumont researchers found that salivary molecules hold promise as reliable diagnostic biomarkers.

    “We used metabolomics, a newer technique to study molecules involved in metabolism,” explained senior study investigator Stewart Graham, Ph.D., assistant professor at Oakland University William Beaumont School of Medicine. “Our goal was to find unique patterns of molecules in the saliva of our study participants that could be used to diagnose Alzheimer’s disease in the earliest stages when treatment is considered most effective. Currently, therapies for Alzheimer’s are initiated only after a patient is diagnosed, and treatments offer modest benefits.”

    In the current study, 29 adults were divided into three groups: mild cognitive impairment, Alzheimer’s disease, and a control group. After specimens were collected, the researchers positively identified and accurately quantified 57 metabolites. Some of the observed variances in the biomarkers were significant. From their data, the research team was able to make predictions as to those at most risk of developing Alzheimer’s.

    “We accurately identified significant concentration changes in 22 metabolites in the saliva of mild cognitive impairment and Alzheimer’s disease patients compared to controls,” the authors wrote. “This pilot study demonstrates the potential for using metabolomics and saliva for the early diagnosis of Alzheimer’s disease.

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