Stability analysis of chemically modified mRNA using micropattern-based single-cell arrays.

The measurement of mRNA turnover in living cells plays an important role in the search for stable mRNA constructs for RNA-based therapies. Here we show that automated time-lapse microscopy combined with micropatterned arrays allows for efficient high-throughput monitoring of fluorescent reporter protein expression at the single-cell level. The fluorescence time courses after mRNA transfection yield the distribution of individual mRNA expression and degradation rates within a population. We compare mRNA constructs with combinations of 5' and 3' UTR sequences and find a systematic broadening and shift towards longer functional half-lives for UTR stabilized mRNA. At the same time the life time distribution of the destabilized EGFP reporter protein was found to be constant and narrowly distributed. Using mathematical modeling, we show that mRNA functional life-time predicts the time-integrated protein level, i.e. the area under the curve (AUC) of mRNA translation. Our approach paves the way for quantitative assessment of hitherto unexplored mRNA functional life time heterogeneity, possibly predicated on multiple mRNA secondary structures and its dependence on UTR sequences.

Multi-level kinetic model of mRNA delivery via transfection of lipoplexes.

Recent work on the use of mRNA lipoplexes for gene delivery demonstrates the need for a mathematical model that simulates and predicts kinetics and transfection efficiency. The small copy numbers involved make it necessary to use stochastic models and include statistical analysis of the variation observed in the experimental data. The modeling requirements are further complicated by the multi-level nature of the problem, where mRNA molecules are contained in lipoplexes, which are in turn contained in endosomes, where each of these entities displays a behavior of its own. We have created a mathematical model that reproduces both the time courses and the statistical variance observed in recent experiments using single-cell tracking of GFP expression after transfection. By applying a few key simplifications and assumptions, we have limited the number of free parameters to five, which we optimize to match five experimental determinants by means of a simulated annealing algorithm. The models demonstrate the need for modeling of nested species in order to reproduce the shape of the dose-response and expression-level curves.

Single-cell mRNA transfection studies: delivery, kinetics and statistics by numbers.

In artificial gene delivery, messenger RNA (mRNA) is an attractive alternative to plasmid DNA (pDNA) since it does not require transfer into the cell nucleus. Here we show that, unlike for pDNA transfection, the delivery statistics and dynamics of mRNA-mediated expression are generic and predictable in terms of mathematical modeling. We measured the single-cell expression time-courses and levels of enhanced green fluorescent protein (eGFP) using time-lapse microscopy and flow cytometry (FC). The single-cell analysis provides direct access to the distribution of onset times, life times and expression rates of mRNA and eGFP. We introduce a two-step stochastic delivery model that reproduces the number distribution of successfully delivered and translated mRNA molecules and thereby the dose-response relation. Our results establish a statistical framework for mRNA transfection and as such should advance the development of RNA carriers and small interfering/micro RNA-based drugs. FROM THE CLINICAL EDITOR: This team of authors established a statistical framework for mRNA transfection by using a two-step stochastic delivery model that reproduces the number distribution of successfully delivered and translated mRNA molecules and thereby their dose-response relation. This study establishes a nice connection between theory and experimental planning and will aid the cellular delivery of mRNA molecules.