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

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

What Determines the Adoption of Digital Innovations by Digital Natives? – The Role of Motivational Affordances

Previous IS research analyzing the adoption of digital innovations has not yet distinguished between digital natives and digital immigrants. Thus, there is still a limited understanding of the special needs regarding digital innovation design and the adoption behavior of individuals identified as digital natives. Therefore, we used a motivational theory perspective from psychological studies to examine the individual needs of digital natives concerning the design of a digital innovation. We conducted a mental simulation experiment with 637 participants. Our findings shed light on the importance of digital nativeness as a predictor of attitudes towards using digital innovations, and the relevance of applying socio-psychological design principles for developing digital innovations

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

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

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

AbstractIn 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 EditorThis 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

Contact-controlled amoeboid motility induces dynamic cell trapping in 3D-microstructured surfaces.

On flat substrates, several cell types exhibit amoeboid migration, which is characterized by restless stochastic successions of pseudopod protrusions. The orientation and frequency of new membrane protrusions characterize efficient search modes, which can respond to external chemical stimuli as observed during chemotaxis in amoebae. To quantify the influence of mechanical stimuli induced by surface topography on the migration modes of the amoeboid model organism Dictyostelium discoideum, we apply high resolution motion analysis in microfabricated pillar arrays of defined density and geometry. Cell motion is analyzed by a two-state motility-model, distinguishing directed cellular runs from phases of isotropic migration that are characterized by randomly oriented cellular protrusions. Cells lacking myosin II or cells deprived of microtubules show significantly different behavior concerning migration velocities and migrational angle distribution, without pronounced attraction to pillars. We conclude that microtubules enhance cellular ability to react with external 3D structures. Our experiments on wild-type cells show that the switching from randomly formed pseudopods to a stabilized leading pseudopod is triggered by contact with surface structures. These alternating processes guide cells according to the available surface in their 3D environment, which we observed dynamically and in steady-state situations. As a consequence, cells perform "home-runs" in low-density pillar arrays, crawling from pillar to pillar, with a characteristic dwell time of 75 s. At the boundary between a flat surface and a 3D structured substrate, cells preferentially localize in contact with micropillars, due to the additionally available surface in the microstructured arrays. Such responses of cell motility to microstructures might open new possibilities for cell sorting in surface structured arrays

Predictive Modeling.

<p>All plots show a parameter vs. transfection efficiency (TE, red circles) and protein expression (GFP, green triangles). The lines are linear or exponential fits. A) Incubation time. B) Endosome degradation rate. C) Lysis rate. D) Lipoplex size.</p