Efficient Polymer-Mediated Delivery of Gene-Editing Ribonucleoprotein Payloads through Combinatorial Design, Parallelized Experimentation, and Machine Learning

Non-viral delivery of the CRISPR/Cas system: DNA versus RNA versus RNP

Since its discovery, the CRISPR/Cas technology has rapidly become an essential tool in modern biomedical research. The opportunities to specifically modify and correct genomic DNA has also raised big hope...

Generation of mutant pigs by lipofection-mediated genome editing in embryos

The specificity and efficiency of CRISPR/Cas9 gene-editing systems are determined by several factors, including the mode of delivery, when applied to mammalian embryos. Given the limited time window for delivery, faster and more reliable methods to introduce Cas9-gRNA ribonucleoprotein complexes (RNPs) into target embryos are needed. In pigs, somatic cell nuclear transfer using gene-modified somatic cells and the direct introduction of gene editors into the cytoplasm of zygotes/embryos by microinjection or electroporation have been used to generate gene-edited embryos; however, these strategies require expensive equipment and sophisticated techniques. In this study, we developed a novel lipofection-mediated RNP transfection technique that does not require specialized equipment for the generation of gene-edited pigs and produced no detectable off-target events. In particular, we determined the concentration of lipofection reagent for efficient RNP delivery into embryos and successfully generated MSTN gene-edited pigs (with mutations in 7 of 9 piglets) after blastocyst transfer to a recipient gilt. This newly established lipofection-based technique is still in its early stages and requires improvements, particularly in terms of editing efficiency. Nonetheless, this practical method for rapid and large-scale lipofection-mediated gene editing in pigs has important agricultural and biomedical applications.

Synthetic molecule libraries for nucleic acid delivery: Design parameters in cationic/ionizable lipids and polymers

Recent progress in the design of cationic lipids and polymers has successfully translated nucleic acid drugs into clinical applications, such as the treatment of liver diseases and the prevention of virus infection. Small or large libraries of delivery molecules have been used to find the key chemical structures to protect nucleic acids from nucleases in the extracellular milieu and to facilitate the endosomal escape after endocytosis. This review introduces three essential design parameters (i.e., acid dissociation constant, hydrophobicity, and biodegradability) to develop synthetic molecules for nucleic acid delivery. The significance and mechanism of each parameter are described based on the results obtained from in vitro and in vivo evaluations. Other design parameters were then discussed to create the next generation of delivery molecules for future nucleic acid therapeutics.

Machine-Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis

Modern polymer science suffers from the curse of multidimensionality. The large chemical space imposed by including combinations of monomers into a statistical copolymer overwhelms polymer synthesis and characterization technology and limits the ability to systematically study structure-property relationships. To tackle this challenge in the context of 19F magnetic resonance imaging (MRI) agents, we pursued a computer-guided materials discovery approach that combines synergistic innovations in automated flow synthesis and machine learning (ML) method development. A software-controlled, continuous polymer synthesis platform was developed to enable iterative experimental-computational cycles that resulted in the synthesis of 397 unique copolymer compositions within a six-variable compositional space. The nonintuitive design criteria identified by ML, which were accomplished by exploring <0.9% of the overall compositional space, lead to the identification of >10 copolymer compositions that outperformed state-of-the-art materials.

Polycation-Mediated Transfection: Mechanisms of Internalization and Intracellular Trafficking

Polyplex-mediated gene transfection is now in its' fourth decade of serious research, but the promise of polyplex-mediated gene therapy has yet to fully materialize. Only approximately one in a million applied plasmids actually expresses. A large part of this is due to an incomplete understanding of the mechanism of polyplex transfection. There is an assumption that internalization must follow a canonical mechanism of receptor mediated endocytosis. Herein, we present arguments that untargeted (and most targeted) polyplexes do not utilize these routes. By incorporating knowledge of syndecan-polyplex interactions, we can show that syndecans are the "target" for polyplexes. Further, it is known that free polycations (which disrupt cell-membranes by acid-catalyzed hydrolysis of phospholipid esters) are necessary for (untargeted) endocytosis. This can be incorporated into the model to produce a novel mechanism of endocytosis, which fits the observed phenomenology. After membrane translocation, polyplex containing vesicles reach the endosome after diffusing through the actin mesh below the cell membrane. From there, they are acidified and trafficked toward the lysosome. Some polyplexes are capable of escaping the endosome and unpacking, while others are not. Herein, it is argued that for some polycations, as acidification proceeds the polyplexes excluding free polycations, which disrupt the endosomal membrane by acid-catalyzed hydrolysis, allowing the polyplex to escape. The polyplex's internal charge ratio is now insufficient for stability and it releases plasmids which diffuse to the nucleus. A small proportion of these plasmids diffuse through the nuclear pore complex (NPC), with aggregation being the major cause of loss. Those plasmids that have diffused through the NPC will also aggregate, and this appears to be the reason such a small proportion of nuclear plasmids express mRNA. Thus, the structural features which promote unpacking in the endosome and allow for endosomal escape can be determined, and better polycations can be designed.

Cationic Bottlebrush Polymers Outperform Linear Polycation Analogues for pDNA Delivery and Gene Expression

Cationic polymer vehicles have emerged as promising platforms for nucleic acid delivery because of their scalability, biocompatibility, and chemical versatility. Advancements in synthetic polymer chemistry allow us to precisely tune chemical functionality with various macromolecular architectures to increase the efficacy of nonviral-based gene delivery. Herein, we demonstrate the first cationic bottlebrush polymer-mediated pDNA delivery by comparing unimolecular, synthetically defined bottlebrush polymers to their linear building blocks. We successfully synthesized poly(2-(dimethylamino)ethyl methacrylate) (pDMAEMA) bottlebrushes through ring-opening metathesis polymerization to afford four bottlebrush polymers with systematic increases in backbone degree of polymerization (N_bb = 13, 20, 26, and 37), while keeping the side-chain degree of polymerization constant (N_sc = 57). Physical and chemical properties were characterized, and subsequently, the toxicity and delivery efficiency of pDNA into HEK293 cells were evaluated. The bottlebrush-pDNA complex (bottleplex) with the highest N_bb, BB_37, displayed up to a 60-fold increase in %EGFP+ cells in comparison to linear macromonomer. Additionally, we observed a trend of increasing EGFP expression with increasing polymer molecular weight. Bottleplexes and polyplexes both displayed high pDNA internalization as measured via payload enumeration per cell; however, quantitative confocal analysis revealed that bottlebrushes were able to shuttle pDNA into and around the nucleus more successfully than pDNA delivered via linear analogues. Overall, a canonical cationic monomer, such as DMAEMA, synthesized in the form of cationic bottlebrush polymers proved to be far more efficient in functional pDNA delivery and expression than linear pDMAEMA. This work underscores the importance of architectural modifications and the potential of bottlebrushes to serve as effective biomacromolecule delivery vehicles.

Development of a PointNet for Detecting Morphologies of Self-Assembled Block Oligomers in Atomistic Simulations

Molecular simulations with atomistic or coarse-grained force fields are a powerful approach for understanding and predicting the self-assembly phase behavior of complex molecules. Amphiphiles, block oligomers, and block polymers can form mesophases with different ordered morphologies describing the spatial distribution of the blocks, but entirely amorphous nature for local packing and chain conformation. Screening block oligomer chemistry and architecture through molecular simulations to find promising candidates for functional materials is aided by effective and straightforward morphology identification techniques. Capturing 3-dimensional periodic structures, such as ordered network morphologies, is hampered by the requirement that the number of molecules in the simulated system and the shape of the periodic simulation box need to be commensurate with those of the resulting network phase. Common strategies for structure identification include structure factors and order parameters, but these fail to identify imperfect structures in simulations with incorrect system sizes. Building upon pioneering work by DeFever et al. [Chem. Sci. 2019, 10, 7503-7515] who implemented a PointNet (i.e., a neural network designed for computer vision applications using point clouds) to detect local structure in simulations of single-bead particles and water molecules, we present a PointNet for detection of nonlocal ordered morphologies of complex block oligomers. Our PointNet was trained using atomic coordinates from molecular dynamics simulation trajectories and synthetic point clouds for ordered network morphologies that were absent from previous simulations. In contrast to prior work on simple molecules, we observe that large point clouds with 1000 or more points are needed for the more complex block oligomers. The trained PointNet model achieves an accuracy as high as 0.99 for globally ordered morphologies formed by linear diblock, linear triblock, and 3-arm and 4-arm star-block oligomers, and it also allows for the discovery of emerging ordered patterns from nonequilibrium systems.

Polymeric Delivery of Therapeutic Nucleic Acids

The advent of genome editing has transformed the therapeutic landscape for several debilitating diseases, and the clinical outlook for gene therapeutics has never been more promising. The therapeutic potential of nucleic acids has been limited by a reliance on engineered viral vectors for delivery. Chemically defined polymers can remediate technological, regulatory, and clinical challenges associated with viral modes of gene delivery. Because of their scalability, versatility, and exquisite tunability, polymers are ideal biomaterial platforms for delivering nucleic acid payloads efficiently while minimizing immune response and cellular toxicity. While polymeric gene delivery has progressed significantly in the past four decades, clinical translation of polymeric vehicles faces several formidable challenges. The aim of our Account is to illustrate diverse concepts in designing polymeric vectors towards meeting therapeutic goals of in vivo and ex vivo gene therapy. Here, we highlight several classes of polymers employed in gene delivery and summarize the recent work on understanding the contributions of chemical and architectural design parameters. We touch upon characterization methods used to visualize and understand events transpiring at the interfaces between polymer, nucleic acids, and the physiological environment. We conclude that interdisciplinary approaches and methodologies motivated by fundamental questions are key to designing high-performing polymeric vehicles for gene therapy.

Automation and data-driven design of polymer therapeutics

Polymers are uniquely suited for drug delivery and biomaterial applications due to tunable structural parameters such as length, composition, architecture, and valency. To facilitate designs, researchers may explore combinatorial libraries in a high throughput fashion to correlate structure to function. However, traditional polymerization reactions including controlled living radical polymerization (CLRP) and ring-opening polymerization (ROP) require inert reaction conditions and extensive expertise to implement. With the advent of air-tolerance and automation, several polymerization techniques are now compatible with well plates and can be carried out at the benchtop, making high throughput synthesis and high throughput screening (HTS) possible. To avoid HTS pitfalls often described as "fishing expeditions," it is crucial to employ intelligent and big data approaches to maximize experimental efficiency. This is where the disruptive technologies of machine learning (ML) and artificial intelligence (AI) will likely play a role. In fact, ML and AI are already impacting small molecule drug discovery and showing signs of emerging in drug delivery. In this review, we present state-of-the-art research in drug delivery, gene delivery, antimicrobial polymers, and bioactive polymers alongside data-driven developments in drug design and organic synthesis. From this insight, important lessons are revealed for the polymer therapeutics community including the value of a closed loop design-build-test-learn workflow. This is an exciting time as researchers will gain the ability to fully explore the polymer structural landscape and establish quantitative structure-property relationships (QSPRs) with biological significance.

Biomedically Relevant Applications of Bolaamphiphiles and Bolaamphiphile-Containing Materials

Bolaamphiphiles (BAs) are structurally segmented molecules with rich assembly characteristics and diverse physical properties. Interest in BAs as standalone active agents or as constituents of more complex therapeutic formulations has increased substantially in recent years. The preorganized amphiphilicity of BAs allows for a range of biological activities including applications that rely on multivalency. This review summarizes BA-related research in biomedically relevant areas. In particular, we review BA-related literature in four areas: gene delivery, antimicrobial materials, hydrogels, and prodrugs. We also discuss several distinguishing characteristics of BAs that impact their utility as biomedically relevant compounds.