Designed proteins induce the formation of nanocage-containing extracellular vesicles

Abstract

Complex biological processes are often performed by self-organizing nanostructures comprising multiple classes of macromolecules, such as ribosomes (proteins and RNA) or enveloped viruses (proteins, nucleic acids, and lipids). Approaches have been developed for designing self-assembling structures consisting of either nucleic acids1,2 or proteins3–5, but strategies for engineering hybrid biological materials are only beginning to emerge6,7. Here, we describe the design of self-assembling protein nanocages that direct their own release from human cells inside small vesicles in a manner that resembles some viruses. We refer to these hybrid biomaterials as Enveloped Protein Nanocages (EPNs). Robust EPN biogenesis required protein sequence elements that encode three distinct functions: membrane binding, self-assembly, and recruitment of the Endosomal Sorting Complexes Required for Transport (ESCRT) machinery8. A variety of synthetic proteins with these functional elements induced EPN biogenesis, highlighting the modularity and generality of the design strategy. Biochemical and electron cryomicroscopic (cryo-EM) analyses revealed that one design, EPN-01, comprised small (~100 nm) vesicles containing multiple protein nanocages that closely matched the structure of the designed 60-subunit self-assembling scaffold9. EPNs that incorporated the vesicular stomatitis viral glycoprotein (VSV-G) could fuse with target cells and deliver their contents, thereby transferring cargoes from one cell to another. These studies show how proteins can be programmed to direct the formation of hybrid biological materials that perform complex tasks, and establish EPNs as a novel class of designed, modular, genetically-encoded nanomaterials that can transfer molecules between cells.

VPS37A directs ESCRT recruitment for phagophore closure

“…ON-TARGETplus SMART Pool nontargeting (D-001810-10) and CHMP2A (L-020247-01) siRNAs were purchased from GE Healthcare. The following plasmids were obtained from Hartmut Land (University of Rochester Medical Center, Rochester, NY), Jay Morgenstern (Imperial Cancer Research Fund, London, UK), Bob Weinberg (Whitehead Institute for Biomedical Research, Cambridge, MA), Feng Zhang (Massachusetts Institute of Technology, Cambridge, MA), Brett Stringer (QIMR Berghofer Medical Research Institute, Brisbane, Australia), Christopher Vakoc (Cold Spring Harbor Laboratory, Cold Spring Harbor, NY), Noboru Mizushima (The University of Tokyo, Tokyo, Japan), Wesley Sundquist (University of Utah School of Medicine, Salt Lake City, UT), Konrad Buessow (Max Planck Institute for Molecular Genetics, Berlin, Germany), and Hemmo Meyer (University of Duisburg-Essen, Essen, Germany) through Addgene: pBabe-Hygro (#1765; Morgenstern and Land, 1990), lentiCas9-Blast (#52962; Sanjana et al, 2014), lentiCRISPRv2 (puro; #98290; Brett Stringer Lab), LRG (Lenti_sgRNA_EFS_GFP, #65656; Shi et al, 2015), pMXs-IP-EGFP-mATG5 (#38196; Hara et al, 2008), pMXs-IP-EGFP-ULK1 (#38193; Hara et al, 2008), pMXs-IP-EGFP-LC3 (#38195; Hara et al, 2008), pEGFP-VPS4-E228Q (#80351; Votteler et al, 2016), pQTEV-VPS28 (#34803; Büssow et al, 2005), and pmCherry-GAL3 (#85662; Papadopoulos et al, 2017). To generate pCDH1-CMV-MCS-SV40-Hygro, the puromycin resistance gene (BamHI–SalI [blunted] in pCDH1-CMV-MCS1-EF1-Puro; #CD510A-1; System Biosciences) was replaced to the hygromycin resistance gene (BanHI–ClaI [blunted]) from pBabe-Hygro.…”

Membrane remodelling by a lipidated endosomal sorting complex required for transport-III chimera, in vitro

“…The modular nature of ESCRT-III components is such that it is possible to swap between the proteins' functional features such as membrane binding, and recognition motifs for Vps4 and still end up with active ESCRT-III chimeras [38]. We hypothesized that a unique ESCRT-III component could be designed by combining the element of membrane recognition by Vps20 ( figure 1b), into the oligomerization potential offered by the Snf7 sequence.…”

DeepScreen: An Accurate, Rapid, and Anti‐Interference Screening Approach for Nanoformulated Medication by Deep Learning

“…The increasing novel nanocarriers study requires the new screening method not only being able to analyze the common nanomaterials, but also the coming promising nanocarriers such as modularized extracellular vehicles (EVs) 49, 50. EVs are nanosized cell‐derived vesicles which could be used to load small molecular drug, RNA, protein, etc., the growing attention of EVs poses a challenge to DeepScreen .…”