Delivery of biomolecules to plants relies on Agrobacterium infection or biolistic particle delivery, the former of which is amenable only to DNA delivery. The difficulty in delivering functional biomolecules such as RNA to plant cells is due to the plant cell wall, which is absent in mammalian cells and poses the dominant physical barrier to biomolecule delivery in plants. DNA nanostructure-mediated biomolecule delivery is an effective strategy to deliver cargoes across the lipid bilayer of mammalian cells; however, nanoparticle-mediated delivery without external mechanical aid remains unexplored for biomolecule delivery across the cell wall in plants. Herein, we report a systematic assessment of different DNA nanostructures for their ability to internalize into cells of mature plants, deliver siRNAs, and effectively silence a constitutively expressed gene in Nicotiana benthamiana leaves. We show that nanostructure internalization into plant cells and corresponding gene silencing efficiency depends on the DNA nanostructure size, shape, compactness, stiffness, and location of the siRNA attachment locus on the nanostructure. We further confirm that the internalization efficiency of DNA nanostructures correlates with their respective gene silencing efficiencies but that the endogenous gene silencing pathway depends on the siRNA attachment locus. Our work establishes the feasibility of biomolecule delivery to plants with DNA nanostructures and both details the design parameters of importance for plant cell internalization and also assesses the impact of DNA nanostructure geometry for gene silencing mechanisms.
Type III-A CRISPR-Cas systems are prokaryotic RNA-guided adaptive immune systems that use a protein-RNA complex, Csm, for transcription-dependent immunity against foreign DNA. Csm can cleave RNA and single-stranded DNA (ssDNA), but whether it targets one or both nucleic acids during transcription elongation is unknown. Here, we show that binding of a Thermus thermophilus (T . thermophilus ) Csm (TthCsm) to a nascent transcript in a transcription elongation complex (TEC) promotes tethering but not direct contact of TthCsm with RNA polymerase (RNAP). Biochemical experiments show that both TthCsm and Staphylococcus epidermidis ( S. epidermidis ) Csm (SepCsm) cleave RNA transcripts, but not ssDNA, at the transcription bubble. Taken together, these results suggest that Type III systems primarily target transcripts, instead of unwound ssDNA in TECs, for immunity against double-stranded DNA (dsDNA) phages and plasmids. This reveals similarities between Csm and eukaryotic RNA interference, which also uses RNA-guided RNA targeting to silence actively transcribed genes.
Genetic engineering of plants is at the core of sustainability efforts, natural product synthesis, and agricultural crop engineering. The plant cell wall is often a barrier that limits the ease and throughput with which exogenous biomolecules can be delivered to plants. Current delivery techniques suffer from host range limitations, low transformation efficiencies, toxicity, and unavoidable DNA integration into the host genome. Here, we demonstrate efficient diffusionbased biomolecule delivery into several species of mature plants with a suite of pristine and chemically-functionalized high aspect ratio nanomaterials. Efficient DNA delivery and strong transient protein expression is accomplished in mature Eruca sativa (arugula-dicot) and Triticum aestivum (wheat-monocot) leaves and protoplasts. We also demonstrate a second nanoparticlebased strategy in which small interfering RNA (siRNA) is delivered to mature Nicotiana benthamiana leaves, to effectively silence a gene with 95% efficiency. Our work provides a tool for species-independent, targeted, and passive delivery of genetic material, without transgene integration, into plant cells for diverse plant biotechnology applications.All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/179549 doi: bioRxiv preprint first posted online Aug. 22, 2017; 2 Plant biotechnology is critical to address the world's leading challenges in meeting our growing food and energy demands, and as a tool for scalable pharmaceutical manufacturing.Over the past several decades, remarkable progress has been made in biotechnology with the improvement of genome editing and sequencing tools. Owing to these recent advancements, plant synthetic biology and bioengineering now has tremendous potential to benefit many fields.In agriculture, genetic enhancement of plants can be employed to create crops that are resistant to herbicides 1 , insects 2 , diseases 3 , and drought. 4 In pharmaceuticals and therapeutics, genetically engineered plants can be used to synthesize valuable small-molecule drugs and recombinant proteins 5 . Furthermore, bioengineered plants may provide cleaner and more efficient biofuels 6,7 .Despite several decades of advancements in biotechnology, most plant species remain difficult to genetically transform 8 . One of the major challenges facing efficient plant genetic transformation is biomolecule delivery into plant cells through the rigid and multi-layered cell wall. Currently, few delivery tools exist that can transfer biomolecules into plant cells, each with considerable limitations. Agrobacterium-mediated delivery 9 is the most commonly used tool for gene delivery into plants with limitations of efficient delivery to only a narrow range of plant species, inability to perform DNA-free editing, unsuitability for high-throughput applications, and unavoidable DNA integration in...
Quantifying RNAs in their spatial context is crucial to understanding gene expression and regulation in complex tissues. In situ transcriptomic methods generate spatially resolved RNA profiles in intact tissues. However, there is a lack of a unified computational framework for integrative analysis of in situ transcriptomic data. Here, we introduce an unsupervised and annotation-free framework, termed ClusterMap, which incorporates the physical location and gene identity of RNAs, formulates the task as a point pattern analysis problem, and identifies biologically meaningful structures by density peak clustering (DPC). Specifically, ClusterMap precisely clusters RNAs into subcellular structures, cell bodies, and tissue regions in both two- and three-dimensional space, and performs consistently on diverse tissue types, including mouse brain, placenta, gut, and human cardiac organoids. We demonstrate ClusterMap to be broadly applicable to various in situ transcriptomic measurements to uncover gene expression patterns, cell niche, and tissue organization principles from images with high-dimensional transcriptomic profiles.
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