an-optimized-mouse-embryonic-stem-cell-based-reverse-poly

An Optimized Mouse Embryonic Stem Cell Based Reverse Poly-Transfection Technique for Rapid Exploration of Nucleic Acid Ratios

Due to its relative simplicity and ease of use, transient transfection of mammalian cell lines with nucleic acids has become a mainstay in biomedical ...

University of British Columbia

New fundamental discoveries in stem cell biology have yielded potentially transformative regenerative therapeutics. However, widespread implementation of stem-cell-derived therapeutics remains sporadic. Barriers that impede the development of these therapeutics can be linked to our incomplete understanding of how the regulatory networks that encode stem cell fate govern the development of the complex tissues and organs that are ultimately required for restorative function. Bioengineering tools, strategies and design principles represent core components of the stem cell bioengineering toolbox. Applied to the different layers of complexity present in stem-cell-derived systems - from gene regulatory networks in single stem cells to the systemic interactions of stem-cell-derived organs and tissues - stem cell bioengineering can address existing challenges and advance regenerative medicine and cellular therapies.

Stem cell bioengineering: building from stem cell biology.

Optical micromanipulation has become popular for a wide range of applications. In this work, a new type of optical micromanipulation platform, patterned optoelectronic tweezers (p-OET), is introduced. In p-OET devices, the photoconductive layer (that is continuous in a conventional OET device) is patterned, forming regions in which the electrode layer is locally exposed. It is demonstrated that micropatterns in the photoconductive layer are useful for repelling unwanted particles/cells, and also for keeping selected particles/cells in place after turning off the light source, minimizing light-induced heating. To clarify the physical mechanism behind these effects, systematic simulations are carried out, which indicate the existence of strong nonuniform electric fields at the boundary of micropatterns. The simulations are consistent with experimental observations, which are explored for a wide variety of geometries and conditions. It is proposed that the new technique may be useful for myriad applications in the rapidly growing area of optical micromanipulation.

Patterned Optoelectronic Tweezers: A New Scheme for Selecting, Moving, and Storing Dielectric Particles and Cells.

The ability to generate induced pluripotent stem cells from differentiated cell types has enabled researchers to engineer cell states. Although studies have identified molecular networks that reprogram cells to pluripotency, the cellular dynamics of these processes remain poorly understood. Here, by combining cellular barcoding, mathematical modeling, and lineage tracing approaches, we demonstrate that reprogramming dynamics in heterogeneous populations are driven by dominant "elite" clones. Clones arise a priori from a population of poised mouse embryonic fibroblasts derived from Wnt1-expressing cells that may represent a neural crest-derived population. This work highlights the importance of cellular dynamics in fate programming outcomes and uncovers cell competition as a mechanism by which cells with eliteness emerge to occupy and dominate the reprogramming niche.

Cell competition during reprogramming gives rise to dominant clones.

Microrobotics extends the reach of human-controlled machines to submillimeter dimensions. We introduce a microrobot that relies on optoelectronic tweezers (OET) that is straightforward to manufacture, can take nearly any desirable shape or form, and can be programmed to carry out sophisticated, multiaxis operations. One particularly useful program is a serial combination of "load," "transport," and "deliver," which can be applied to manipulate a wide range of micrometer-dimension payloads. Importantly, microrobots programmed in this manner are much gentler on fragile mammalian cells than conventional OET techniques. The microrobotic system described here was demonstrated to be useful for single-cell isolation, clonal expansion, RNA sequencing, manipulation within enclosed systems, controlling cell-cell interactions, and isolating precious microtissues from heterogeneous mixtures. We propose that the optoelectronic microrobotic system, which can be implemented using a microscope and consumer-grade optical projector, will be useful for a wide range of applications in the life sciences and beyond.

The optoelectronic microrobot: A versatile toolbox for micromanipulation.

In vitro models of postimplantation human development are valuable to the fields of regenerative medicine and developmental biology. Here, we report characterization of a robust in vitro platform that enabled high-content screening of multiple human pluripotent stem cell (hPSC) lines for their ability to undergo peri-gastrulation-like fate patterning upon bone morphogenetic protein 4 (BMP4) treatment of geometrically confined colonies and observed significant heterogeneity in their differentiation propensities along a gastrulation associable and neuralization associable axis. This cell line-associated heterogeneity was found to be attributable to endogenous Nodal expression, with up-regulation of Nodal correlated with expression of a gastrulation-associated gene profile, and Nodal down-regulation correlated with a preneurulation-associated gene profile expression. We harness this knowledge to establish a platform of preneurulation-like fate patterning in geometrically confined hPSC colonies in which fates arise because of a BMPs signalling gradient conveying positional information. Our work identifies a Nodal signalling-dependent switch in peri-gastrulation versus preneurulation-associated fate patterning in hPSC cells, provides a technology to robustly assay hPSC differentiation outcomes, and suggests conserved mechanisms of organized fate specification in differentiating epiblast and ectodermal tissues.

High-throughput micropatterning platform reveals Nodal-dependent bisection of peri-gastrulation-associated versus preneurulation-associated fate patterning.

Superspreaders (individuals with a high propensity for disease spread) have played a pivotal role in recent emerging and re-emerging diseases. In disease outbreak studies, host heterogeneity based on demographic (e.g. age, sex, vaccination status) and environmental (e.g. climate, urban/rural residence, clinics) factors are critical for the spread of infectious diseases, such as Ebola and Middle East Respiratory Syndrome (MERS). Transmission rates can vary as demographic and environmental factors are altered naturally or due to modified behaviors in response to the implementation of public health strategies. In this work, we develop stochastic models to explore the effects of demographic and environmental variability on human-to-human disease transmission rates among superspreaders in the case of Ebola and MERS. We show that the addition of environmental variability results in reduced probability of outbreak occurrence, however the severity of outbreaks that do occur increases. These observations have implications for public health strategies that aim to control environmental variables.

Effects of environmental variability on superspreading transmission events in stochastic epidemic models.

The rise of systems biology has ushered a new paradigm: the view of the cell as a system that processes environmental inputs to drive phenotypic outputs. Synthetic biology provides a complementary approach, allowing us to program cell behavior through the addition of synthetic genetic devices into the cellular processor. These devices, and the complex genetic circuits they compose, are engineered using a design-prototype-test cycle, allowing for predictable device performance to be achieved in a context-dependent manner. Within mammalian cells, context effects impact device performance at multiple scales, including the genetic, cellular, and extracellular levels. In order for synthetic genetic devices to achieve predictable behaviors, approaches to overcome context dependence are necessary. Here, we describe control systems approaches for achieving context-aware devices that are robust to context effects. We then consider cell fate programing as a case study to explore the potential impact of context-aware devices for regenerative medicine applications.

Context-aware synthetic biology by controller design: Engineering the mammalian cell.

Recent advancements in cellular engineering, including reprogramming of somatic cells into pluripotent stem cells, have opened the door to a new era of regenerative medicine. Given that cellular decisions are guided by microenvironmental cues, such as secreted factors and interactions with neighbouring cells, reproducible cell manufacturing requires robust control over cell-cell interactions. Cell competition has recently emerged as a previously unknown interaction that plays a significant role in shaping the growth and death dynamics of multicellular stem cell populations, both in vivo and in vitro. Although recent studies have largely focused on exploring how the differential expression of key genes mediate the competitive elimination of some cells, little is known about the impact of the microenvironment on cell competition, despite its critical role in shaping cell fate outcomes. Here, we explore recent findings that have brought cell competition into the spotlight, while dissecting the role of microenvironmental factors for controlling competition in cell fate programming applications.

Evening the playing field: microenvironmental control over stem cell competition during fate programming.

Stem cells experience many selective pressures which shape their cellular populations, potentially pushing them to skew towards dominance of a few break-through clones. An evolutionarily conserved answer to curb these aberrant selective pressures is cell competition, the elimination of a subset of cells by their neighbours in a seemingly homogenous population. Cell competition in mammalian systems is a relatively recent discovery that has now been observed across many tissue systems, such as embryonic, haematopoietic, intestinal, and epithelial compartments. With this rapidly growing field, there is a need to revisit and standardize the terminology used, much of which has been co-opted from evolutionary biology. Further, the implications of cell competition across biological scales in organisms have been difficult to capture. In this review, we make three key points. One, we propose new nomenclature to standardize concepts across dispersed studies of different types of competition, each of which currently use the same terminology to describe different phenomena. Second, we highlight the challenges in capturing information flow across biological scales. Third, we challenge the field to incorporate next generation technologies into the cell competition toolkit to bridge these gaps. As the field of cell competition matures, synergy between cutting edge tools will help elucidate the molecular events which shape cellular growth and death dynamics, allowing a deeper examination of this evolutionarily conserved mechanism at the core of multicellularity.

The Field of Cell Competition Comes of Age: Semantics and Technological Synergy.

The dynamic nature of the COVID-19 pandemic has demanded a public health response that is constantly evolving due to the novelty of the virus. Many jurisdictions in the USA, Canada, and across the world have adopted social distancing and recommended the use of face masks. Considering these measures, it is prudent to understand the contributions of subpopulations-such as "silent spreaders"-to disease transmission dynamics in order to inform public health strategies in a jurisdiction-dependent manner. Additionally, we and others have shown that demographic and environmental stochasticity in transmission rates can play an important role in shaping disease dynamics. Here, we create a model for the COVID-19 pandemic by including two classes of individuals: silent spreaders, who either never experience a symptomatic phase or remain undetected throughout their disease course; and symptomatic spreaders, who experience symptoms and are detected. We fit the model to real-time COVID-19 confirmed cases and deaths to derive the transmission rates, death rates, and other relevant parameters for multiple phases of outbreaks in British Columbia (BC), Canada. We determine the extent to which SilS contributed to BC's early wave of disease transmission as well as the impact of public health interventions on reducing transmission from both SilS and SymS. To do this, we validate our model against an existing COVID-19 parameterized framework and then fit our model to clinical data to estimate key parameter values for different stages of BC's disease dynamics. We then use these parameters to construct a hybrid stochastic model that leverages the strengths of both a time-nonhomogeneous discrete process and a stochastic differential equation model. By combining these previously established approaches, we explore the impact of demographic and environmental variability on disease dynamics by simulating various scenarios in which a COVID-19 outbreak is initiated. Our results demonstrate that variability in disease transmission rate impacts the probability and severity of COVID-19 outbreaks differently in high- versus low-transmission scenarios.

A Hybrid Epidemic Model to Explore Stochasticity in COVID-19 Dynamics.

Revealing the molecular events associated with reprogramming different somatic cell types to pluripotency is critical for understanding the characteristics of induced pluripotent stem cell (iPSC) therapeutic derivatives. Inducible reprogramming factor transgenic cells or animals-designated as secondary (2°) reprogramming systems-not only provide excellent experimental tools for such studies but also offer a strategy to study the variances in cellular reprogramming outcomes due to different in vitro and in vivo environments. To make such studies less cumbersome, it is desirable to have a variety of efficient reprogrammable mouse systems to induce successful mass reprogramming in somatic cell types. Here, we report the development of two transgenic mouse lines from which 2° cells reprogram with unprecedented efficiency. These systems were derived by exposing primary reprogramming cells containing doxycycline-inducible Yamanaka factor expression to a transient interruption in transgene expression, resulting in selection for a subset of clones with robust transgene response. These systems also include reporter genes enabling easy readout of endogenous  activation (GFP), indicative of pluripotency, and reprogramming transgene expression (mCherry). Notably, somatic cells derived from various fetal and adult tissues from these 2° mouse lines gave rise to highly efficient and rapid reprogramming, with transgene-independent iPSC colonies emerging as early as 1 wk after induction. These mouse lines serve as a powerful tool to explore sources of variability in reprogramming and the mechanistic underpinnings of efficient reprogramming systems.

Highly efficient reprogrammable mouse lines with integrated reporters to track the route to pluripotency.

Reprogramming human fibroblasts to induced pluripotent stem cells (iPSCs) is inefficient, with heterogeneity among transcription factor (TF) trajectories driving divergent cell states. Nevertheless, the impact of TF dynamics on reprogramming efficiency remains uncharted. Here, we identify the successful reprogramming trajectories of the core pluripotency TF, OCT4, and design a genetic controller that enforces such trajectories with high precision. By combining a genetic circuit that generates a wide range of OCT4 trajectories with live-cell imaging, we track OCT4 trajectories with clonal resolution and find that a distinct constant OCT4 trajectory is required for colony formation. We then develop a synthetic genetic circuit that yields a tight OCT4 distribution around the identified trajectory and outperforms in terms of reprogramming efficiency other circuits that less accurately regulate OCT4. Our synthetic biology approach is generalizable for identifying and enforcing TF dynamics for cell fate programming applications.

Synthetic genetic circuits to uncover and enforce the OCT4 trajectories of successful reprogramming of human fibroblasts.

Tenure time loopers.

Reprogramming human fibroblasts to induced pluripotent stem cells (iPSCs) is inefficient, with heterogeneity among transcription factor (TF) trajectories driving divergent cell states. Nevertheless, the impact of TF dynamics on reprogramming efficiency remains uncharted. We develop a system that accurately reports OCT4 protein levels in live cells and use it to reveal the trajectories of OCT4 in successful reprogramming. Our system comprises a synthetic genetic circuit that leverages noise to generate a wide range of OCT4 trajectories and a microRNA targeting endogenous OCT4 to set total cellular OCT4 protein levels. By fusing OCT4 to a fluorescent protein, we are able to track OCT4 trajectories with clonal resolution via live-cell imaging. We discover that a supraphysiological, stable OCT4 level is required, but not sufficient, for efficient iPSC colony formation. Our synthetic genetic circuit design and high-throughput live-imaging pipeline are generalizable for investigating TF dynamics for other cell fate programming applications.

Nika Shakiba

School of Biomedical Engineering

University of British Columbia

An Optimized Mouse Embryonic Stem Cell Based Reverse Poly-Transfection Technique for Rapid Exploration of Nucleic Acid Ratios

Nika Shakiba

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}School of Biomedical Engineering

University of British Columbia

An Optimized Mouse Embryonic Stem Cell Based Reverse Poly-Transfection Technique for Rapid Exploration of Nucleic Acid Ratios

School of Biomedical Engineering