From Clipping Scissors to Word Processor: New Platform Transforms CRISPR Gene Editor Into Precision Tool

Barcodes are used in a new way in the MAGESTIC platform, adding a new level of precision to CRISPR gene editing.  Credit: Kelly Irvine/NIST

Barcodes are used in a new way in the MAGESTIC platform, adding a new level of precision to CRISPR gene editing.

Credit: Kelly Irvine/NIST

Using the gene-editing tool CRISPR to snip at DNA is often akin to using scissors to edit a newspaper article. You can cut out words, but it’s difficult to remove individual letters or instantly know how the cuts affect the meaning of the text. Someday, CRISPR could be used to “clip” disease-causing genetic mutations in patients. But such precision medicine is impossible so long as CRISPR remains a clumsy tool.

In work that will help make the gene-editing process more precise, researchers at the Joint Initiative for Metrology in Biology (JIMB, a collaboration between Stanford University and the National Institute of Standards and Technology, or NIST), have developed a new kind of CRISPR platform called MAGESTIC. Taking its name from the phrase “multiplexed accurate genome editing with short, trackable, integrated cellular barcodes,” the new platform makes CRISPR less like a blunt cutting tool and more like a word processor by enabling an efficient “search and replace” function for genetic material. Announced today in a Nature Biotechnology paper(link is external), MAGESTIC also produced a sevenfold increase in cell survival during the editing process.

“MAGESTIC is like an advancement in the ‘control F’ [Find Text] operation of a word-processing program, with the replace-text command allowing a desired change. This lets us really poke at the cell in a very precise way and see how the change affects cell function. Then we can compare the actual effects of each variant with the computationally predicted effects, and ultimately improve models for predicting how genetic variants impact health and disease,” said JIMB scientist Kevin Roy, a MAGESTIC developer.

Being able to precisely edit genomes with CRISPR requires an extensive understanding of how cells will repair cuts at different sites across the genome so that you can control the process as needed. Currently, random mutations can occur at cut sites in the cell’s DNA, often because the DNA strands rejoin in unpredictable ways. What’s more, lots of cells don’t survive the editing process at all. Building accurate predictions for gene editing remains, therefore, extremely challenging.

What researchers want is a reliable way to program the CRISPR machinery to cut at desired locations throughout the genome, and then to direct the cells to introduce designed edits at the DNA cut sites. This can be done by providing the cell with a “donor” DNA that the cell’s DNA repair machinery can use as a template to replace the original sequence at the cut site. This is not unlike what editors often do to revise a text, first searching for a certain word or sequence of words and then replacing it with something else. However, the DNA repair system inside the cell is complex and does not always behave predictably like a word processor.

The process by which the cell searches for a suitable donor DNA to repair a cut site is an enormous challenge for the cell, as the DNA repair machinery must search among millions to billions of base pairs of DNA sequence to find the correct “donor” DNA. MAGESTIC provides a major advance in gene-editing technology, aiding the cell in this search by artificially recruiting the designed donor DNA directly to the cut site in a process termed “active donor recruitment.”

Such recruitment caused a sevenfold increase in cell survival, a change that surprised the research team with its efficiency and effectiveness.

Another one of the main features that separates MAGESTIC from previous approaches with multiplexed CRISPR editing is a new kind of cellular barcode. Researchers have traditionally used small bits of circular DNA, known as plasmids, to express the guide RNAs and to store barcodes to track the designed mutations in each cell. The plasmids multiply as the cell grows and are inherited by both cells after cell division. In theory, they should act much like the black-and-white barcodes used to track items at the checkout stand. But unlike the single-barcode-per-item correspondence at the checkout stand, the plasmid barcodes can vary widely in number, with anywhere from 10–40 appearing in each cell. That can give an inaccurate measure of cell abundance. In MAGESTIC, barcodes are integrated into chromosomes instead. This makes them stable and easy to find and count later.

Although many advances have been made in DNA sequencing and editing over the last two decades, general understanding of the function of genomic sequence remains sparse. Scientists know very little about the function of the 0.1 percent of code that varies between individuals in a population and is responsible for differences in disease susceptibility.

MAGESTIC will help to address this gap in the understanding of natural genetic variation by enabling each genetic variant to be precisely edited and compared to other genetic variants one-by-one. This helps to uncover which genetic differences have an impact on cellular function. MAGESTIC also performs all edits at once in a single test tube, with each edit occurring in any one of millions of otherwise identical cells. This is more efficient than past platforms, which required editing for each variant in separate experiments.

“We are reaching a state where we have not only achieved the ability to sequence the order of base pairs in genomes but we can also make changes to them. We still need a better understanding of the consequences of our edits,” said JIMB’s Lars Steinmetz, professor of genetics at Stanford University, group leader at the European Molecular Biology Laboratory (EMBL), and senior author on the paper. “With MAGESTIC it’s like being able to make small edits to individual letters in a book, and being able to see what effect it has on the meaning of the text. Our donor recruitment method also allows the new piece of information to be placed at exactly the right page where the cut occurred.”

Bringing together NIST scientists and industry entrepreneurs, JIMB creates new standards, measurement tools and methods to support research, innovation and widespread adoption of bioscience advances. Other experts on the MAGESTIC team included researchers from the EMBLTexas A&M University and Brandeis University.

Paper: K. Roy, J. Smith, S. Vonesch, G. Lin, C.S. Tu, A. Lederer, A. Chu, S. Suresh, M. Nguyen, J. Horecka, A. Tripathi, W.T. Burnett, M. Morgan, J. Schulz, K. Orsley, W. Wei, R. Aiyar, R. Davis, V.A. Bankaitis, J. Haber, M. Salit, R. St.Onge, and L. Steinmetz. Multiplexed precision genome editing with trackable genomic barcodes in yeast. Nature Biotechnology. 7 May 2018. DOI: 10.1038/nbt4137

Benchmarking Samples to Help Understand the Reliability of Genome-Scale RNA Measurements Published by NIST's JIMB team

NIST Special Publication 1200-23: Preparation of a Set of Total RNA Benchmarking Samples for Performance Assessment of Genome-scale Differential Gene Expression Version 1.0 


A variety of technologies have been developed for genome-scale profiling of differential gene expression. The level of gene expression difference is typically reported in the form of a ratio, comparing one sample (or class of samples) to another. Studies to develop cancer biomarkers typically involve comparing tumor tissue to normal tissue and identifying features that distinguish the two classes. However, most published cancer biomarkers never make it into clinical practice [1], with a major technical challenge being the irreproducibility of results [2]. A set of papers describes assessing technical performance using sets of mixed total RNA samples designed with between-sample differences in the relative abundance of mRNA [3-7]. Recent work within the Early Detection Research Network (EDRN) of the National Cancer Institute [8] has used these mixed sample sets for measurement assurance of genome-scale microRNA (miRNA) biomarker discovery. This protocol presents a general procedure for the preparation of these mixture sets, for any biomolecule cohort (e.g. mRNA, proteins, etc.), provided mixture components are available that express different abundances of the molecules.

The full publication is available here.

‘Start Codons’ in DNA and RNA May Be More Numerous Than Previously Thought


For decades, scientists working with genetic material have labored with a few basic rules in mind. To start, DNA is transcribed into messenger RNA (mRNA), and mRNA is translated into proteins, which are essential for almost all biological functions. A central principle regarding translation has long held that only a small number of three-letter sequences in mRNA, known as start codons, could trigger the production of proteins. But researchers might need to revisit and possibly rewrite this rule, after recent measurements from a team including scientists from the National Institute of Standards and Technology (NIST)

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President Obama Honors Federally-Funded Early-Career Scientists, Including JIMB Team Member Justin Zook

The White House

Office of the Press Secretary

For Immediate Release

January 09, 2017

President Obama Honors Federally-Funded Early-Career Scientists

Today, President Obama named 102 scientists and researchers as recipients of the Presidential Early Career Awards for Scientists and Engineers (PECASE), the highest honor bestowed by the United States Government on science and engineering professionals in the early stages of their independent research careers.
“I congratulate these outstanding scientists and engineers on their impactful work,” President Obama said. “These innovators are working to help keep the United States on the cutting edge, showing that Federal investments in science lead to advancements that expand our knowledge of the world around us and contribute to our economy.”
The Presidential Early Career Awards highlight the key role that the Administration places in encouraging and accelerating American innovation to grow our economy and tackle our greatest challenges. This year’s recipients are employed or funded by the following departments and agencies: Department of Agriculture, Department of Commerce, Department of Defense, Department of Education, Department of Energy, Department of Health and Human Services, Department of the Interior, Department of Veterans Affairs, Environmental Protection Agency, National Aeronautics and Space Administration, National Science Foundation, Smithsonian Institution, and the Intelligence Community. These departments and agencies join together annually to nominate the most meritorious scientists and engineers whose early accomplishments show the greatest promise for assuring America’s preeminence in science and engineering and contributing to the awarding agencies' missions.
The awards, established by President Clinton in 1996, are coordinated by the Office of Science and Technology Policy within the Executive Office of the President. Awardees are selected for their pursuit of innovative research at the frontiers of science and technology and their commitment to community service as demonstrated through scientific leadership, public education, or community outreach.
The newest recipients are:
Department of Agriculture
Michelle Cilia, USDA Agricultural Research Service
Pankaj Lal, Montclair State University
Michael Ulyshen, USDA Forest Service
Department of Commerce

Nicholas Butch, NIST Center for Neutron Research
Mandy Karnauskas, NOAA Fisheries
Anne Perring, University of Colorado, Boulder
Corey Potvin, University of Oklahoma
John Teufel, NIST Physical Measurement Laboratory
Justin Zook, NIST Material Measurement Laboratory
Department of Defense
Michael Bell, Colorado State University
Nurcin Celik, University of Miami
Kaushik Chowdhury, Northeastern University
Shawn Douglas, University of California, San Francisco
Christopher Dyer, DeepMind and Carnegie Mellon University
Aaron Esser-Kahn, University of California, Irvine
Sinan Keten, Northwestern University
Jonathan Fan, Stanford University
Danna Freedman, Northwestern University
Thomas Harris, Northwestern University
David Hsieh, California Institute of Technology
Osama Nayfeh, Space and Naval Warfare Systems Center-Pacific
Olukayode Okusaga, Johns Hopkins Applied Physics Laboratory
Joseph Parker, U.S. Naval Research Laboratory
Adam Pilchak, Air Force Research Laboratory
Harris Wang, Columbia University
Department of Education
Daphna Bassok, University of Virginia
Shayne Piasta, The Ohio State University
Department of Energy
Jonathan Belof, Lawrence Livermore National Laboratory
Carl Dahl, Northwestern University
Eric Duoss, Lawrence Livermore National Laboratory
Anna Grassellino, Fermi National Accelerator Laboratory
Jacqueline Hakala, National Energy Technology Laboratory
Stephanie Hansen, Sandia National Laboratories
Kory Hedman, Arizona State University
Alan Kruizenga, Sandia National Laboratories
Wei Li, Rice University
Guglielmo Scovazzi, Duke University
Michael Tonks, Penn State University
Jenny Yang, University of California, Irvine
John Yeager, Los Alamos National Laboratory
Department of Health and Human Services
Gregory Alushin, Rockefeller University
Manish Arora, Icahn School of Medicine at Mount Sinai
Dawn Cornelison, University of Missouri
Kashmira Date, Centers for Disease Control and Prevention
Craig Duvall, Vanderbilt University
Nicholas Gilpin, Louisiana State University Health Sciences Center
Anna Greka, Brigham and Women's Hospital
Pamela Guerrerio, National Institutes of Health
Gery Guy, Jr., Centers for Disease Control and Prevention
Christine Hendon, Columbia University
Catherine Karr, University of Washington
Maria Lehtinen, Boston Children's Hospital
Adriana Lleras-Muney, University of California, Los Angeles
Mary Kay Lobo, University of Maryland School of Medicine
Michael McAlpine, University of Minnesota
Eric Morrow, Brown University
Daniel O'Connor, Johns Hopkins University
Aimee Shen, Tufts University
Cui Tao, University of Texas
Jacquelyn Taylor, Yale School of Nursing
Benjamin Voight, University of Pennsylvania
Matthew Wheeler, Centers for Disease Control and Prevention
Blake Wiedenheft, Montana State University
Department of Interior
Nathaniel Hitt, U.S. Geological Survey
Sarah Minson, U.S. Geological Survey
Diann Prosser, U.S. Geological Survey
Department of Veterans Affairs
Adam Rose, RAND Corporation and Boston Medical Center
Nasia Safdar, Middleton Memorial Veterans Hospital
Joshua Yarrow, U.S. Department of Veterans Affairs
Environmental Protection Agency
Havala Pye, Environmental Protection Agency
Sala Senkayi, Environmental Protection Agency
Intelligence Community
Matthew Dicken, U.S. Army
Josiah Dykstra, National Security Agency
James Kang, National Geospatial-Intelligence Agency
Jason Matheny, Office of the Director of National Intelligence
David Moehring, IonQ, Inc.
R. Jacob Vogelstein, Intelligence Advanced Research Projects Activity
National Aeronautics and Space Administration
Jeremy Bassis, University of Michigan
Othmane Benafan, NASA Glenn Research Center
Dalia Kirschbaum, NASA Goddard Space Flight Center
Marco Pavone, Stanford University
Miguel Roman, NASA Goddard Space Flight Center
National Science Foundation
Alicia Alonzo, Michigan State University
Randy Ewoldt, University of Illinois at Urbana-Champaign
Emily Fox, University of Washington
Jacob Fox, Stanford University
Eric Hudson, University of California, Los Angeles
Shawn Jordan, Arizona State University
Ahmed Khalil, Boston University
Oleg Komogortsev, Texas State University, San Marcos
John Kovac, Harvard University
Bérénice Mettler, University of Minnesota and icuemotion, LLC
Jelani Nelson, Harvard University
Elizabeth Nolan, Massachusetts Institute of Technology
Michael Rotkowitz, University of Maryland, College Park
Andrea Sweigart, University of Georgia
Chuanbing Tang, University of South Carolina
Aradhna Tripati, University of California, Los Angeles
Franck Vernerey, University of Colorado, Boulder
Juan Pablo Vielma Centeno, Massachusetts Institute of Technology
Makeba Wilbourn, Duke University
Smithsonian Institution
Nicholas Pyenson, Smithsonian Institution

NIST Releases New 'Family' of Standardized Genomes

With the addition of four new reference materials (RMs) to a growing collection of “measuring sticks” for gene sequencing, the National Institute of Standards and Technology (NIST) can now provide laboratories with even more capability to accurately “map” DNA for genetic testing, medical diagnoses and future customized drug therapies. The new tools feature sequenced genes from individuals in two genetically diverse groups, Asians and Ashkenazic Jews; a father-mother-child trio set from Ashkenazic Jews; and four microbes commonly used in research.

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BioRxiv Pre-Print: Genome-wide reconstruction of complex structural variants using read clouds

Recently developed methods that utilize partitioning of long genomic DNA fragments, and barcoding of shorter fragments derived from them, have succeeded in retaining long-range information in short sequencing reads. These so-called read cloud approaches represent a powerful, accurate, and cost-effective alternative to single-molecule long-read sequencing. We developed software, GROC-SVs, that takes advantage of read clouds for structural variant detection and assembly.

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BioRxiv Pre-Print: Measurements of translation initiation from all 64 codons in E. coli

Our understanding of translation is one cornerstone of molecular biology that underpins our capacity to engineer living matter. The canonical start codon (AUG) and a few near-cognates (GUG, UUG) are typically considered as the start codons for translation initiation in Escherichia coli (E. coli). Translation is typically not thought to initiate from the 61 remaining codons. Here, we systematically quantified translation initiation in E. coli from all 64 triplet codons. We detected protein synthesis above background initiating from at least 46 codons. Translation initiated from these non-canonical start codons at levels ranging from 0.01% to 2% relative to AUG. Translation initiation from non-canonical start codons may contribute to the synthesis of peptides in both natural and synthetic biological systems.

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Journal of the American Chemical Society Publication: In Vivo Site-Specific Protein Tagging with Diverse Amines Using an Engineered Sortase Variant

Chemoenzymatic modification of proteins is an attractive option to create highly specific conjugates for therapeutics, diagnostics, or materials under gentle biological conditions. However, these methods often suffer from expensive specialized substrates, bulky fusion tags, low yields, and extra purification steps to achieve the desired conjugate. Staphylococcus aureus sortase A and its engineered variants are used to attach oligoglycine derivatives to the C-terminus of proteins expressed with a minimal LPXTG tag. This strategy has been used extensively for bioconjugation in vitro and for proteinprotein conjugation in living cells. Here we show that an enzyme variant recently engineered for higher activity on oligoglycine has promiscuous activity that allows proteins to be tagged using a diverse array of small, commercially available amines, including several bioorthogonal func- tional groups. This technique can also be carried out in living Escherichia coli, enabling simple, inexpensive production of chemically functionalized proteins with no additional purification steps. 

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ACS Synthetic Biology Publication: When Wavelengths Collide: Bias in Cell Abundance Measurements Due to Expressed Fluorescent Proteins

The abundance of bacteria in liquid culture is commonly inferred by measuring optical density at 600 nm. Red fluorescent proteins (RFPs) can strongly absorb light at 600 nm. Increasing RFP expression can falsely inflate apparent cell density and lead to underestimations of mean per-cell fluorescence by up to 10%. Measuring optical density at 700 nm would allow estimation of cell abundance unaffected by the presence of nearly all fluorescent proteins. 

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