Dataset Information

Combinatorial approach to determine functional group effects on lipidoid-mediated siRNA delivery.

ABSTRACT: The application of RNA interference (RNAi), either in the clinic or in the laboratory, requires safe and effective delivery methods. Here, we develop a combinatorial approach to synthesize a library of delivery vectors based on two lipid-like substrates with known siRNA delivery capabilities. Members of this library have a mixture of lipid-like tails and feature appendages containing hydroxyl, carbamate, ether, or amine functional groups as well as variations in alkyl chain length and branching. Using a luciferase reporter system in HeLa cells, we studied the relationship between lipid chemical modification and delivery performance in vitro. The impact of the functional group was shown to vary depending on the overall amine content and tail number of the delivery vector. Additionally, in vivo performance was evaluated using a Factor VII knockdown assay. Two library members, each containing ether groups, were found to knock down the target protein at levels comparable to those of the parent delivery vector. These results demonstrate that small chemical changes to the delivery vector impact knockdown efficiency and cell viability both in vitro and in vivo. The work described here identifies new materials for siRNA delivery and provides new insight into the parameters for optimized chemical makeup of lipid-like siRNA delivery materials.

SUBMITTER: Mahon KP

PROVIDER: S-EPMC2931596 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Combinatorial approach to determine functional group effects on lipidoid-mediated siRNA delivery.

Mahon Kerry P KP Love Kevin T KT Whitehead Kathryn A KA Qin June J Akinc Akin A Leshchiner Elizaveta E Leshchiner Ignaty I Langer Robert R Anderson Daniel G DG

Bioconjugate chemistry 20100801 8

The application of RNA interference (RNAi), either in the clinic or in the laboratory, requires safe and effective delivery methods. Here, we develop a combinatorial approach to synthesize a library of delivery vectors based on two lipid-like substrates with known siRNA delivery capabilities. Members of this library have a mixture of lipid-like tails and feature appendages containing hydroxyl, carbamate, ether, or amine functional groups as well as variations in alkyl chain length and branching. ...[more]

PMID: 20715849

Similar Datasets

Project description:The ability to coat scaffolds and wound dressings with therapeutic short interfering RNA (siRNA) holds much potential for applications in wound healing, cancer treatment, and regenerative medicine. Layer-by-layer (LbL) technology is an effective method to formulate polyelectrolyte thin films for local delivery of siRNA; however, the formation and efficacy of LbL coatings as drug delivery systems are highly contingent on the assembly conditions. Here, we investigate the effects of LbL assembly parameters on film composition and consequent siRNA-mediated gene knockdown efficiency in vitro. Films comprising poly(β-amino ester) (PBAE) and siRNA were built on polyglactin 910 (Vicryl) sutures consisting of poly(10% L-lactide, 90% glycolide). A fractional factorial design was employed, varying the following LbL assembly conditions: pH, ionic strength, PBAE concentration, and siRNA concentration. Effects of these parameters on PBAE loading, siRNA loading, their respective weight ratios, and in vitro siRNA-mediated knockdown were elucidated. The parameter effects were leveraged to create a rationally designed set of solution conditions that was predicted to give effective siRNA-mediated knockdown, but not included in any of the original experimental conditions. This level of knockdown with our rationally designed loading conditions (47%) is comparable to previous formulations from our lab while being simpler in construction and requiring fewer film layers, which could save time and cost in manufacturing. This study highlights the importance of LbL solution conditions in the preparation of surface-mediated siRNA delivery systems and presents an adaptable methodology for extending these electrostatically-assembled coatings to the delivery of other therapeutic nucleic acids. STATEMENT OF SIGNIFICANCE: Short interfering RNA (siRNA) therapeutics are powerful tools to silence aberrant gene expression in the diseased state; however, the clinical utility of these therapies relies on effective controlled delivery approaches. Electrostatic self-assembly through the layer-by-layer (LbL) process enables direct siRNA release from surfaces, but this method is highly dependent upon the specific solution conditions used. Here, we use a fractional factorial design to illustrate how these assembly conditions impact composition of siRNA-eluting LbL thin films. We then elucidate how these properties mediate in vitro transfection efficacy. Ultimately, this work presents a significant step towards understanding how optimization of assembly conditions for surface-mediated LbL delivery can promote transfection efficacy while reducing the processing and material required.

Project description:MOTIVATION:Perturbation experiments constitute the central means to study cellular networks. Several confounding factors complicate computational modeling of signaling networks from this data. First, the technique of RNA interference (RNAi), designed and commonly used to knock-down specific genes, suffers from off-target effects. As a result, each experiment is a combinatorial perturbation of multiple genes. Second, the perturbations propagate along unknown connections in the signaling network. Once the signal is blocked by perturbation, proteins downstream of the targeted proteins also become inactivated. Finally, all perturbed network members, either directly targeted by the experiment, or by propagation in the network, contribute to the observed effect, either in a positive or negative manner. One of the key questions of computational inference of signaling networks from such data are, how many and what combinations of perturbations are required to uniquely and accurately infer the model? RESULTS:Here, we introduce an enhanced version of linear effects models (LEMs), which extends the original by accounting for both negative and positive contributions of the perturbed network proteins to the observed phenotype. We prove that the enhanced LEMs are identified from data measured under perturbations of all single, pairs and triplets of network proteins. For small networks of up to five nodes, only perturbations of single and pairs of proteins are required for identifiability. Extensive simulations demonstrate that enhanced LEMs achieve excellent accuracy of parameter estimation and network structure learning, outperforming the previous version on realistic data. LEMs applied to Bartonella henselae infection RNAi screening data identified known interactions between eight nodes of the infection network, confirming high specificity of our model and suggested one new interaction. AVAILABILITY AND IMPLEMENTATION:https://github.com/EwaSzczurek/LEM. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

Dataset Information

Combinatorial approach to determine functional group effects on lipidoid-mediated siRNA delivery.

Publications

Combinatorial approach to determine functional group effects on lipidoid-mediated siRNA delivery.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets