The use of mRNA for therapeutic purposes has gained significant attention due to its potential to treat a wide range of diseases, including cancer, infectious diseases, and genetic disorders. However, the efficient delivery of mRNA to target cells remains a major challenge, and delivery of mRNA faces major issues such as rapid degradation and poor cellular uptake. Aminoglycoside-derived lipopolymer nanoparticles (LPNs) have been shown as a promising platform for plasmid DNA (pDNA) delivery due to their stability, biocompatibility, and ability to encapsulate mRNA. The current study aims to develop and optimize LPNs formulation for the delivery of mRNA in aggressive cancer cells, using a combination of chemical synthesis, physicochemical characterization, and in vitro biological assays. From a small library of aminoglycoside-derived lipopolymers, the lead lipopolymers were screened for the efficient delivery of mRNA. The complexes were synthesized with different ratios of lipopolymers to mRNA. The appropriate binding ratios of lipopolymers and mRNA were determined by gel electrophoresis. The complexes were characterized using dynamic light scattering (DLS) and zeta potential. The transgene expression efficacy of polymers was evaluated using in vitro bioluminescence assay. The toxicity of LPNs and LPNs-mRNA complexes was evaluated using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The current study comprehensively investigates the optimization of the LPNs-mRNA formulation for enhanced efficacy in transgene expression in human advanced-stage melanoma cell lines.

Single cell heterogeneity plays an important role in the onset and progression of a variety of disease pathologies. One of the most notable examples of the impact of heterogeneity in the complexity of a disease is cancer. Traditionally, molecular analyses on cancer-related samples have been performed on bulk populations of cells, with the resultant data only representative of an average of the population, thereby concealing potentially relevant information about individual cells. Performing these studies at the single cell level is proposed to address this issue. However, current methods for the isolation and analysis of single cells often require specialized and expensive equipment that may be prohibitive to labs wishing to perform such analyses. Herein, a method for the isolation and gene expression analysis of single cells is described that (1) relies only on readily available, inexpensive materials, (2) is compatible with phase and fluorescent microscopy, and (3) allows for the ability to track specific cells throughout all measurements. This method utilizes random seeding of single cells on 72-well Terasaki plates (also called microtest plates) that have 20 µl, optically clear flat-bottomed wells in order to circumvent the need for specific hardware for cell isolation. Suspensions of the Barrett’s esophagus epithelial cell line CP-D stably expressing turboGFP and a related, GFP-negative BE cell line, CP-A, were prepared, seeded at a concentration of approximately 1-2 cells/well and incubated overnight. Wells containing single cells were visually identified using phase-contrast and fluorescent microscopy. Single cells were then lysed directly in the well, total RNA was isolated, and RT-qPCR was performed. RT-qPCR results reflected the ability to distinguish between turboGFP-expressing and non-expressing cells that matched previous identification by microscopy. These results indicate that this is a convenient and cost-effective method for studying gene expression in single cells.

Background: Heterogeneity within cell populations is relevant to the onset and progression of disease, as well as development and maintenance of homeostasis. Analysis and understanding of the roles of heterogeneity in biological systems require methods and technologies that are capable of single cell resolution. Single cell gene expression analysis by RT-qPCR is an established technique for identifying transcriptomic heterogeneity in cellular populations, but it generally requires specialized equipment or tedious manipulations for cell isolation.

Results: We describe the optimization of a simple, inexpensive and rapid pipeline which includes isolation and culture of live single cells as well as fluorescence microscopy and gene expression analysis of the same single cells by RT-qPCR. We characterize the efficiency of single cell isolation and demonstrate our method by identifying single GFP-expressing cells from a mixed population of GFP-positive and negative cells by correlating fluorescence microscopy and RT-qPCR.

Conclusions: Single cell gene expression analysis by RT-qPCR is a convenient means for investigating cellular heterogeneity, but is most useful when correlating observations with additional measurements. We demonstrate a convenient and simple pipeline for multiplexing single cell RT-qPCR with fluorescence microscopy which is adaptable to other molecular analyses.