Water Droplets Hold the Secret Ingredient for Building Life. Chemists uncover key to early Earth chemistry, which could unlock paths to speed up chemical synthesis for…
Category: bioengineering – Page 81
A team of researchers at Northwestern University has devised a new platform for gene editing that could inform the future application of a near-limitless library of CRISPR-based therapeutics.
Using chemical design and synthesis, the team brought together the Nobel-prize winning technology with therapeutic technology born in their own lab to overcome a critical limitation of CRISPR. Specifically, the groundbreaking work provides a system to deliver the cargo required for generating the gene editing machine known as CRISPR-Cas9. The team developed a way to transform the Cas-9 protein into a spherical nucleic acid (SNA) and load it with critical components as required to access a broad range of tissue and cell types, as well as the intracellular compartments required for gene editing.
The research, published today in a paper titled, “CRISPR Spherical Nucleic Acids,” in the publication Journal of the American Chemical Society, and shows how CRISPR SNAs can be delivered across the cell membrane and into the nucleus while also retaining bioactivity and gene editing capabilities.
This video is the 1st of a series of “What is Aging” webinars that aims to unravel what aging is, how we age, why we age, and how to reverse it.
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Accurate detection and manipulation of endogenous proteins is essential to understand cell biological processes, which motivated laboratories across cell biology to develop highly efficient CRISPR genome editing methods for endogenous epitope tagging (Auer et al., 2014; Nakade et al., 2014; Lackner et al., 2015; Schmid-Burgk et al., 2016; Suzuki et al., 2016; Nishiyama et al., 2017; Artegiani et al., 2020; Danner et al., 2021). Multiplex editing using NHEJ-based CRISPR/Cas9 methods remains limited because of the high degree of cross talk that occurs between two knock-in loci (Gao et al., 2019; Willems et al., 2020). In the current study we present CAKE, a mechanism to diminish cross talk between NHEJ-based CRISPR/Cas9 knock-ins using sequential activation of gRNA expression. We demonstrate that this mechanism strongly reduces cross talk between knock-in loci, and results in dual knock-ins for a wide variety of genes. Finally, we showed that CAKE can be directly applied to reveal new biological insights. CAKE allowed us to perform two-color super-resolution microscopy and acute manipulation of the dynamics of endogenous proteins in neurons, together revealing new insights in the nanoscale organization of synaptic proteins.
The CAKE mechanism presented here creates a mosaic of CreON and CreOFF knock-ins, and the number of double knock-in cells depends on the efficacy of each knock-in vector. Therefore, to obtain a high number of double knock-in cells, the efficacy of both the CreON and CreOFF knock-in vector must be optimized. We identified three parameters that regulate the efficacy for single and double knock-ins in neurons. First, the efficacy of gRNAs varies widely, and even gRNAs that target sequences a few base pairs apart in the same locus can have dramatically different knock-in rates (Willems et al., 2020; Danner et al., 2021; Fang et al., 2021; Zhong et al., 2021). Thus, the efficacy of each individual gRNA must be optimized to increase the chance of successful multiplex labeling in neurons. gRNA performance is dependent on many factors, including the rate of DNA cleavage and repair (Rose et al., 2017; Liu et al., 2020; Park et al.
The complexity of life on Earth was derived from simplicity: From the first protocells to the growth of any organism, individual cells aggregate into basic clumps and then form more complex structures. The earliest cells lacked complicated biochemical machinery; to evolve into multicellular organisms, simple mechanisms were necessary to produce chemical signals that prompted the cells to both move and form colonies.
Replicating this behavior in synthetic systems is necessary to advance fields such as soft robotics. Chemical engineering researchers at the University of Pittsburgh Swanson School of Engineering have established this feat in their latest advancement in biomimicry.
The research, “Lifelike behavior of chemically oscillating mobile capsules,” was published in the journal Matter. The lead author is Oleg E. Shklyaev, post-doctoral associate with Anna Balazs, Distinguished Professor of Chemical and Petroleum Engineering and the John A. Swanson Chair of Engineering.
Thanks to new RNA vaccines, we humans have been able to protect ourselves incredibly quickly from new viruses like SARS-CoV-2, the virus that causes COVID-19. These vaccines insert a piece of ephemeral genetic material into the body’s cells, which then read its code and churn out a specific protein—in this case, telltale “spikes” that stud the outside of the coronavirus—priming the immune system to fight future invaders.
The technique is effective, and has promise for all sorts of therapies, says Eerik Kaseniit, Ph.D. student in bioengineering at Stanford. At the moment, though, these sorts of RNA therapies can’t focus on specific cells. Once injected into the body, they indiscriminately make the encoded protein in every cell they enter. If you want to use them to treat only one kind of cell—like those inside a cancerous tumor—you’ll need something more precise.
Kaseniit and his advisor, assistant professor of chemical engineering Xiaojing Gao, may have found a way to make this possible. They’ve created a new tool called an RNA “sensor”—a strand of lab-made RNA that reveals its contents only when it enters particular tissues within the body. The method is so exact that it can home in on both cell types and cell states, activating only when its target cell is creating a certain RNA, says Gao. The pair published their findings Oct. 5 in the journal Nature Biotechnology.
Although just cute little creatures at first glance, the microscopic geckos and octopuses fabricated by 3D laser printing in the molecular engineering labs at Heidelberg University could open up new opportunities in fields such as microrobotics or biomedicine.
The printed microstructures are made from novel materials —known as smart polymers—whose size and mechanical properties can be tuned on demand and with high precision. These “life-like” 3D microstructures were developed in the framework of the “3D Matter Made to Order” (3DMM2O) Cluster of Excellence, a collaboration between Ruperto Carola and the Karlsruhe Institute of Technology (KIT).
“Manufacturing programmable materials whose mechanical properties can be adapted on demand is highly desired for many applications,” states Junior Professor Dr. Eva Blasco, group leader at the Institute of Organic Chemistry and the Institute for Molecular Systems Engineering and Advanced Materials of Heidelberg University.
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In a discovery with wide-ranging implications, researchers at the University of Massachusetts Amherst recently announced in the Proceedings of the National Academy of Sciences that uniformly charged macromolecules—or molecules, such as proteins or DNA, that contain a large number of atoms all with the same electrical charge—can self-assemble into very large structures. This finding upends our understanding of how some of life’s basic structures are built.
Traditionally, scientists have understood charged polymer chains as being composed of smaller, uniformly charged units. Such chains, called polyelectrolytes, display predictable behaviors of self-organization in water: They will repel each other because similarly charged objects don’t like to be close to each other. If you add salt to water containing polyelectrolytes, then molecules coil up, because the chains’ electrical repulsion is screened by the salt.
However, “the game is very different when you have dipoles,” says Murugappan Muthukumar, the Wilmer D. Barrett Professor in Polymer Science and Engineering at UMass Amherst, the study’s senior author.
This year’s Breakthrough Prize in Life Sciences has a strong physical sciences element. The prize was divided between six individuals. Demis Hassabis and John Jumper of the London-based AI company DeepMind were awarded a third of the prize for developing AlphaFold, a machine-learning algorithm that can accurately predict the 3D structure of proteins from just the amino-acid sequence of their polypeptide chain. Emmanuel Mignot of Stanford University School of Medicine and Masashi Yanagisawa of the University of Tsukuba, Japan, were awarded for their work on the sleeping disorder narcolepsy.
The remainder of the prize went to Clifford Brangwynne of Princeton University and Anthony Hyman of the Max Planck Institute of Molecular Cell Biology and Genetics in Germany for discovering that the molecular machinery within a cell—proteins and RNA—organizes by phase separating into liquid droplets. This phase separation process has since been shown to be involved in several basic cellular functions, including gene expression, protein synthesis and storage, and stress responses.
The award for Brangwynne and Hyman shows “the transformative role that the physics of soft matter and the physics of polymers can play in cell biology,” says Rohit Pappu, a biophysicist and bioengineer at Washington University in St. Louis. “[The discovery] could only have happened the way it did: a creative young physicist working with an imaginative cell biologist in an ecosystem where boundaries were always being pushed at the intersection of multiple disciplines.”