bims-novged 2023-01-29 papers

bims-novged

Biomed News

on Non-viral vectors for gene delivery

Issue of 2023–01–29
eleven papers selected by
the Merkel lab, Ludwig-Maximilians University

Ionizable lipid nanoparticles deliver mRNA to pancreatic β cells via macrophage-mediated gene transfer.
Comparison of tyrosine-modified low molecular weight branched and linear polyethylenimines for siRNA delivery.
Diosgenin enhances liposome-enabled nucleic acid delivery and CRISPR/Cas9-mediated gene editing by modulating endocytic pathways.
The Transcriptional Response to Lung-Targeting Lipid Nanoparticles in Vivo.
Radiolabeled Biodistribution of Expansile Nanoparticles: Intraperitoneal Administration Results in Tumor Specific Accumulation.
3D RNA-scaffolded wireframe origami.
Monitoring the in vivo siRNA release from lipid nanoparticles based on the fluorescence resonance energy transfer principle.
Nanoparticle biodistribution coefficients: A quantitative approach for understanding the tissue distribution of nanoparticles.
Data-Driven Design of Polymer-Based Biomaterials: High-throughput Simulation, Experimentation, and Machine Learning.
Machine learning in the development of targeting microRNAs in human disease.
Interaction of gentamicin and gentamicin-AOT with poly-(lactide-co-glycolate) in a drug delivery system - density functional theory calculations and molecular dynamics simulation.

Sci Adv. 2023 Jan 27. 9(4): eade1444

Ionizable lipid nanoparticles deliver mRNA to pancreatic β cells via macrophage-mediated gene transfer.

Jilian R Melamed, Saigopalakrishna S Yerneni, Mariah L Arral, Samuel T LoPresti, Namit Chaudhary, Anuradha Sehrawat, Hiromi Muramatsu, Mohamad-Gabriel Alameh, Norbert Pardi, Drew Weissman, George K Gittes, Kathryn A Whitehead.

Systemic messenger RNA (mRNA) delivery to organs outside the liver, spleen, and lungs remains challenging. To overcome this issue, we hypothesized that altering nanoparticle chemistry and administration routes may enable mRNA-induced protein expression outside of the reticuloendothelial system. Here, we describe a strategy for delivering mRNA potently and specifically to the pancreas using lipid nanoparticles. Our results show that delivering lipid nanoparticles containing cationic helper lipids by intraperitoneal administration produces robust and specific protein expression in the pancreas. Most resultant protein expression occurred within insulin-producing β cells. Last, we found that pancreatic mRNA delivery was dependent on horizontal gene transfer by peritoneal macrophage exosome secretion, an underappreciated mechanism that influences the delivery of mRNA lipid nanoparticles. We anticipate that this strategy will enable gene therapies for intractable pancreatic diseases such as diabetes and cancer.

DOI: https://doi.org/10.1126/sciadv.ade1444
Nanotoxicology. 2023 Jan 25. 1-16

Comparison of tyrosine-modified low molecular weight branched and linear polyethylenimines for siRNA delivery.

Małgorzata Kubczak, Sylwia Michlewska, Michael Karimov, Alexander Ewe, Achim Aigner, Maria Bryszewska, Maksim Ionov.

  Polyethylenimines (PEIs) have been previously introduced for siRNA delivery. In particular, in the case of higher molecular weight PEIs, this is associated with toxicity, while low molecular weight PEIs are often insufficient for siRNA complexation. The tyrosine-modification of PEIs has been shown to enhance PEI efficacy and biocompatibility. This paper evaluates a set of tyrosine-modified low molecular weight linear or branched polyethylenimines as efficient carriers of siRNA. Complexation efficacies and biophysical complex properties were analyzed by zeta potential, dynamic light scattering and circular dichroism measurements as well as gel electrophoresis. Biological knockdown was studied in 2 D cell culture and 3 D ex vivo tissue slice air-liquid interface culture. The results demonstrate that siRNAs were able to form stable complexes with all tested polymers. Complexation was able to protect siRNA from degradation by RNase and to mediate target gene knockdown, as determined on the mRNA level and in PC3-Luc3/EGFP and HCT116-Luc3/EGFP expressing reporter cells on the protein level, using flow cytometry and confocal microscopy. The direct comparison of the studied polymers revealed differences in biological efficacies. Moreover, the tyrosine-modified PEIs showed high biocompatibility, as determined by LDH release and mitochondria integrity (J-aggregate assay) as well as caspase 3/7 (apoptosis) and H2O2 levels (ROS). In 3 D tissue slices, complexes based on LP10Y proved to be most efficient, by combining tissue penetration with efficient gene expression knockdown.

Keywords:  Nanomaterials; gene knockdown cytotoxicity; polyethylenimines; polymeric nanoparticles; siRNA delivery

DOI:  https://doi.org/10.1080/17435390.2022.2159891
Front Bioeng Biotechnol. 2022 ;10 1031049

Diosgenin enhances liposome-enabled nucleic acid delivery and CRISPR/Cas9-mediated gene editing by modulating endocytic pathways.

Brijesh Lohchania, Abisha Crystal Christopher, Porkizhi Arjunan, Gokulnath Mahalingam, Durga Kathirvelu, Aishwarya Prasannan, Vigneshwaran Venkatesan, Pankaj Taneja, Mohan Kumar Km, Saravanabhavan Thangavel, Srujan Marepally.

  The CRISPR/Cas9 system holds great promise in treating genetic diseases, owing to its safe and precise genome editing. However, the major challenges to implementing the technology in clinics lie in transiently limiting the expression of genome editing factors and achieving therapeutically relevant frequencies with fidelity. Recent findings revealed that non-viral vectors could be a potential alternative delivery system to overcome these limitations. In our previous research, we demonstrated that liposomal formulations with amide linker-based cationic lipids and cholesterol were found to be effective in delivering a variety of nucleic acids. In the current study, we screened steroidal sapogenins as an alternative co-lipid to cholesterol in cationic liposomal formulations and found that liposomes with diosgenin (AD, Amide lipid: Diosgenin) further improved nucleic acid delivery efficacy, in particular, delivering Cas9 pDNA and mRNA for efficient genome editing at multiple loci, including AAVS1 and HBB, when compared to amide cholesterol. Mechanistic insights into the endocytosis of lipoplexes revealed that diosgenin facilitated the lipoplexes' cholesterol-independent and clathrin-mediated endocytosis, which in turn leads to increased intracellular delivery. Our study identifies diosgenin-doped liposomes as an efficient tool to deliver CRISPR/Cas9 system.

Keywords:  CRISPR/Cas9; cationic lipid; diosgenin; genome editing; transfections

DOI:  https://doi.org/10.3389/fbioe.2022.1031049
Nano Lett. 2023 Jan 26.

The Transcriptional Response to Lung-Targeting Lipid Nanoparticles in Vivo.

Afsane Radmand, Melissa P Lokugamage, Hyejin Kim, Curtis Dobrowolski, Ryan Zenhausern, David Loughrey, Sebastian G Huayamares, Marine Z C Hatit, Huanzhen Ni, Ada Del Cid, Alejandro J Da Silva Sanchez, Kalina Paunovska, Elisa Schrader Echeverri, Aram Shajii, Hannah Peck, Philip J Santangelo, James E Dahlman.

  Lipid nanoparticles (LNPs) have delivered RNA to hepatocytes in patients, underscoring the potential impact of nonliver delivery. Scientists can shift LNP tropism to the lung by adding cationic helper lipids; however, the biological response to these LNPs remains understudied. To evaluate the hypothesis that charged LNPs lead to differential cellular responses, we quantified how 137 LNPs delivered mRNA to 19 cell types in vivo. Consistent with previous studies, we observed helper lipid-dependent tropism. After identifying and individually characterizing three LNPs that targeted different tissues, we studied the in vivo transcriptomic response to these using single-cell RNA sequencing. Out of 835 potential pathways, 27 were upregulated in the lung, and of these 27, 19 were related to either RNA or protein metabolism. These data suggest that endogenous cellular RNA and protein machinery affects mRNA delivery to the lung in vivo.

Keywords:  DNA barcode; LNP; lipid nanoparticle; mRNA; scRNA-seq; single-cell RNA sequencing

DOI:  https://doi.org/10.1021/acs.nanolett.2c04479
ACS Nano. 2023 Jan 26.

Radiolabeled Biodistribution of Expansile Nanoparticles: Intraperitoneal Administration Results in Tumor Specific Accumulation.

Aaron H Colby, Jack Kirsch, Amit N Patwa, Rong Liu, Beth Hollister, William McCulloch, Joanna E Burdette, Cedric J Pearce, Nicholas H Oberliels, Yolonda L Colson, Kebin Liu, Mark W Grinstaff.

  Nanoparticle biodistribution in vivo is an essential component to the success of nanoparticle-based drug delivery systems. Previous studies with fluorescently labeled expansile nanoparticles, or "eNPs", demonstrated a high specificity of eNPs to tumors that is achieved through a materials-based targeting strategy. However, fluorescent labeling techniques are primarily qualitative in nature and the gold-standard for quantitative evaluation of biodistribution is through radiolabeling. In this manuscript, we synthesize 14C-labeled eNPs to quantitatively evaluate the biodistribution of these particles in a murine model of intraperitoneal mesothelioma via liquid scintillation counting. The results demonstrate a strong specificity of eNPs for tumors that lasts one to 2 weeks postinjection with an overall delivery efficiency to the tumor tissue of 30% of the injected dose which is congruent with prior reports of preclinical efficacy of the technology. Importantly, the route of administration is essential to the eNP's material-based targeting strategy with intraperitoneal administration leading to tumoral accumulation while, in contrast, intravenous administration leads to rapid clearance via the reticuloendothelial system and low tumoral accumulation. A comparison against nanoparticle delivery systems published over the past decade shows that the 30% tumoral delivery efficiency of the eNP is significantly higher than the 0.7% median delivery efficiency of other systems with sufficient quantitative data to define this metric. These results lay a foundation for targeting intraperitoneal tumors and encourage efforts to explore alternative, nonintravenous routes, of delivery to accelerate the translation of nanoparticle therapies to the clinic.

Keywords:  Radiolabeled biodistribution; expansile nanoparticle; intraperitoneal administration; liquid scintillation counting; materials-based targeting

DOI:  https://doi.org/10.1021/acsnano.2c08451
Nat Commun. 2023 Jan 24. 14(1): 382

3D RNA-scaffolded wireframe origami.

Molly F Parsons, Matthew F Allan, Shanshan Li, Tyson R Shepherd, Sakul Ratanalert, Kaiming Zhang, Krista M Pullen, Wah Chiu, Silvi Rouskin, Mark Bathe.

Hybrid RNA:DNA origami, in which a long RNA scaffold strand folds into a target nanostructure via thermal annealing with complementary DNA oligos, has only been explored to a limited extent despite its unique potential for biomedical delivery of mRNA, tertiary structure characterization of long RNAs, and fabrication of artificial ribozymes. Here, we investigate design principles of three-dimensional wireframe RNA-scaffolded origami rendered as polyhedra composed of dual-duplex edges. We computationally design, fabricate, and characterize tetrahedra folded from an EGFP-encoding messenger RNA and de Bruijn sequences, an octahedron folded with M13 transcript RNA, and an octahedron and pentagonal bipyramids folded with 23S ribosomal RNA, demonstrating the ability to make diverse polyhedral shapes with distinct structural and functional RNA scaffolds. We characterize secondary and tertiary structures using dimethyl sulfate mutational profiling and cryo-electron microscopy, revealing insight into both global and local, base-level structures of origami. Our top-down sequence design strategy enables the use of long RNAs as functional scaffolds for complex wireframe origami.

DOI: https://doi.org/10.1038/s41467-023-36156-1
Asian J Pharm Sci. 2023 Jan;18(1): 100769

Monitoring the in vivo siRNA release from lipid nanoparticles based on the fluorescence resonance energy transfer principle.

Lei Sun, Jinfang Zhang, Jing-E Zhou, Jing Wang, Zhehao Wang, Shenggen Luo, Yeying Wang, Shulei Zhu, Fan Yang, Jie Tang, Wei Lu, Yiting Wang, Lei Yu, Zhiqiang Yan.

  The siRNA-loaded lipid nanoparticles have attracted much attention due to its significant gene silencing effect and successful marketization. However, the in vivo distribution and release of siRNA still cannot be effectively monitored. In this study, based on the fluorescence resonance energy transfer (FRET) principle, a fluorescence dye Cy5-modified survivin siRNA was conjugated to nanogolds (Au-DR-siRNA), which were then wrapped with lipid nanoparticles (LNPs) for monitoring the release behaviour of siRNA in vivo. The results showed that once Au-DR-siRNA was released from the LNPs and cleaved by the Dicer enzyme to produce free siRNA in cells, the fluorescence of Cy5 would change from quenched state to activated state, showing the location and time of siRNA release. Besides, the LNPs showed a significant antitumor effect by silencing the survivin gene and a CT imaging function superior to iohexol by nanogolds. Therefore, this work provided not only an effective method for monitoring the pharmacokinetic behaviour of LNP-based siRNA, but also a siRNA delivery system for treating and diagnosing tumors.

Keywords:  Fluorescence resonance energy transfer; In vivo release; Lipid nanoparticles; Nanogolds; Survivin siRNA

DOI:  https://doi.org/10.1016/j.ajps.2022.11.003
Adv Drug Deliv Rev. 2023 Jan 20. pii: S0169-409X(23)00023-6. [Epub ahead of print]194 114708

Nanoparticle biodistribution coefficients: A quantitative approach for understanding the tissue distribution of nanoparticles.

Mokshada Kumar, Priyanka Kulkarni, Shufang Liu, Nagendra Chemuturi, Dhaval K Shah.

  The objective of this manuscript is to provide quantitative insights into the tissue distribution of nanoparticles. Published pharmacokinetics of nanoparticles in plasma, tumor and 13 different tissues of mice were collected from literature. A total of 2018 datasets were analyzed and biodistribution of graphene oxide, lipid, polymeric, silica, iron oxide and gold nanoparticles in different tissues was quantitatively characterized using Nanoparticle Biodistribution Coefficients (NBC). It was observed that typically after intravenous administration most of the nanoparticles are accumulated in the liver (NBC = 17.56 %ID/g) and spleen (NBC = 12.1 %ID/g), while other tissues received less than 5 %ID/g. NBC values for kidney, lungs, heart, bones, brain, stomach, intestine, pancreas, skin, muscle and tumor were found to be 3.1 %ID/g, 2.8 %ID/g, 1.8 %ID/g, 0.9 %ID/g, 0.3 %ID/g, 1.2 %ID/g, 1.8 %ID/g, 1.2 %ID/g, 1.0 %ID/g, 0.6 %ID/g and 3.4 %ID/g, respectively. Significant variability in nanoparticle distribution was observed in certain organs such as liver, spleen and lungs. A large fraction of this variability could be explained by accounting for the differences in nanoparticle physicochemical properties such as size and material. A critical overview of published nanoparticle physiologically-based pharmacokinetic (PBPK) models is provided, and limitations in our current knowledge about in vitro and in vivo pharmacokinetics of nanoparticles that restrict the development of robust PBPK models is also discussed. It is hypothesized that robust quantitative assessment of whole-body pharmacokinetics of nanoparticles and development of mathematical models that can predict their disposition can improve the probability of successful clinical translation of these modalities.

Keywords:  Biodistribution; Drug delivery; Meta-analysis; Nanomedicine; Nanoparticle; PBPK; Pharmacokinetics; Physiologically based pharmacokinetic modeling; Tissue distribution

DOI:  https://doi.org/10.1016/j.addr.2023.114708
ACS Appl Bio Mater. 2023 Jan 26.

Data-Driven Design of Polymer-Based Biomaterials: High-throughput Simulation, Experimentation, and Machine Learning.

Roshan A Patel, Michael A Webb.

  Polymers, with the capacity to tunably alter properties and response based on manipulation of their chemical characteristics, are attractive components in biomaterials. Nevertheless, their potential as functional materials is also inhibited by their complexity, which complicates rational or brute-force design and realization. In recent years, machine learning has emerged as a useful tool for facilitating materials design via efficient modeling of structure-property relationships in the chemical domain of interest. In this Spotlight, we discuss the emergence of data-driven design of polymers that can be deployed in biomaterials with particular emphasis on complex copolymer systems. We outline recent developments, as well as our own contributions and takeaways, related to high-throughput data generation for polymer systems, methods for surrogate modeling by machine learning, and paradigms for property optimization and design. Throughout this discussion, we highlight key aspects of successful strategies and other considerations that will be relevant to the future design of polymer-based biomaterials with target properties.

Keywords:  active learning; copolymer featurization; high-throughput characterization; polymer automation; polymer biomaterials; polymer design; protein−polymer interactions; structure−property surrogate modeling

DOI:  https://doi.org/10.1021/acsabm.2c00962
Front Genet. 2022 ;13 1088189

Machine learning in the development of targeting microRNAs in human disease.

Yuxun Luo, Li Peng, Wenyu Shan, Mengyue Sun, Lingyun Luo, Wei Liang.

  A microRNA is a small, single-stranded, non-coding ribonucleic acid that plays a crucial role in RNA silencing and can regulate gene expression. With the in-depth study of miRNA in development and disease, miRNA has become an attractive target for novel therapeutic strategies. Exploring miRNA targeting therapy only through experiments is expensive and laborious, so it is essential to develop novel and efficient computational methods to narrow down the search. Recent advances in machine learning applied in biomedical informatics provide opportunities to explore miRNA-targeting drugs, thus promoting miRNA therapeutics. This review provides an overview of recent advancements in miRNA targeting therapeutic using machine learning. First, we mainly describe the basics of predicting miRNA targeting drugs, including pharmacogenomic data resources and data preprocessing. Then we present primary machine learning algorithms and elaborate their application in discovering relationships among miRNAs, drugs, and diseases. Along with the progress of miRNA targeting therapeutics, we finally analyze and discuss the current challenges and opportunities that machine learning confronts.

Keywords:  deep learning; machine learning; miRNA-disease association; miRNA-drug association; mirna therapy

DOI:  https://doi.org/10.3389/fgene.2022.1088189
Biophys Chem. 2023 Jan 14. pii: S0301-4622(23)00009-1. [Epub ahead of print]294 106958

Interaction of gentamicin and gentamicin-AOT with poly-(lactide-co-glycolate) in a drug delivery system - density functional theory calculations and molecular dynamics simulation.

Shahid Duran, Jamshed Anwar, Syed Tarique Moin.

  Gentamicin is used to treat brucellosis, an infectious disease caused by the Brucella species but the drug faces several issues such as low efficacy, instability, low solubility, and toxicity. It also has a very short half-life, therefore, requiring frequent dosing. Consequently, several other antibiotics are also being used for the treatment of brucellosis as a single dose as well as in combination with other antibiotics but none of these therapies are satisfactory. Nanoparticles in particular polymer-based ones utilizing polymers that are biodegradable and biocompatible for instance PLGA are a method of choice to overcome such drug delivery issues and enable potential targeted delivery. The current study focuses on the evaluation of the structural and dynamical properties of a drug-polymer system consisting of gentamicin drug and PLGA polymer nanoparticles in the water representing a targeted drug delivery system for the treatment of brucellosis. For this purpose, all-atom molecular dynamics simulations were carried out on the drug-polymer systems in the absence and presence of the surfactant bis(2-Ethylhexyl) sulfosuccinate (AOT) to determine the structural and dynamical properties as well as the effect of the surfactant on these properties. We also investigated systems in which the polymer constituents were in the form of monomeric units toward decoupling the primary interactions of the monomer units and polymer effects. The simulation results explain the nature of the interactions between the drug and the polymer as well as transport properties in terms of drug diffusion coefficients, which characterize the molecular behavior of gentamicin-polymer nanoparticles for use in brucellosis.

Keywords:  Brucellosis; Diffusion coefficients; Drug delivery system; Gentamicin; Molecular dynamics simulation

DOI:  https://doi.org/10.1016/j.bpc.2023.106958