Reprogramming to recover youthful epigenetic information and restore vision.

Ageing is a degenerative process that leads to tissue dysfunction and death. A proposed cause of ageing is the accumulation of epigenetic noise that disrupts gene expression patterns, leading to decreases in tissue function and regenerative capacity1-3. Changes to DNA methylation patterns over time form the basis of ageing clocks4, but whether older individuals retain the information needed to restore these patterns-and, if so, whether this could improve tissue function-is not known. Over time, the central nervous system (CNS) loses function and regenerative capacity5-7. Using the eye as a model CNS tissue, here we show that ectopic expression of Oct4 (also known as Pou5f1), Sox2 and Klf4 genes (OSK) in mouse retinal ganglion cells restores youthful DNA methylation patterns and transcriptomes, promotes axon regeneration after injury, and reverses vision loss in a mouse model of glaucoma and in aged mice. The beneficial effects of OSK-induced reprogramming in axon regeneration and vision require the DNA demethylases TET1 and TET2. These data indicate that mammalian tissues retain a record of youthful epigenetic information-encoded in part by DNA methylation-that can be accessed to improve tissue function and promote regeneration in vivo.

Regulation of lifespan by neural excitation and REST.

The mechanisms that extend lifespan in humans are poorly understood. Here we show that extended longevity in humans is associated with a distinct transcriptome signature in the cerebral cortex that is characterized by downregulation of genes related to neural excitation and synaptic function. In Caenorhabditis elegans, neural excitation increases with age and inhibition of excitation globally, or in glutamatergic or cholinergic neurons, increases longevity. Furthermore, longevity is dynamically regulated by the excitatory-inhibitory balance of neural circuits. The transcription factor REST is upregulated in humans with extended longevity and represses excitation-related genes. Notably, REST-deficient mice exhibit increased cortical activity and neuronal excitability during ageing. Similarly, loss-of-function mutations in the C. elegans REST orthologue genes spr-3 and spr-4 elevate neural excitation and reduce the lifespan of long-lived daf-2 mutants. In wild-type worms, overexpression of spr-4 suppresses excitation and extends lifespan. REST, SPR-3, SPR-4 and reduced excitation activate the longevity-associated transcription factors FOXO1 and DAF-16 in mammals and worms, respectively. These findings reveal a conserved mechanism of ageing that is mediated by neural circuit activity and regulated by REST.

A single combination gene therapy treats multiple age-related diseases.

Comorbidity is common as age increases, and currently prescribed treatments often ignore the interconnectedness of the involved age-related diseases. The presence of any one such disease usually increases the risk of having others, and new approaches will be more effective at increasing an individual's health span by taking this systems-level view into account. In this study, we developed gene therapies based on 3 longevity associated genes (fibroblast growth factor 21 [FGF21], αKlotho, soluble form of mouse transforming growth factor-ß receptor 2 [sTGFßR2]) delivered using adeno-associated viruses and explored their ability to mitigate 4 age-related diseases: obesity, type II diabetes, heart failure, and renal failure. Individually and combinatorially, we applied these therapies to disease-specific mouse models and found that this set of diverse pathologies could be effectively treated and in some cases, even reversed with a single dose. We observed a 58% increase in heart function in ascending aortic constriction ensuing heart failure, a 38% reduction in α-smooth muscle actin (αSMA) expression, and a 75% reduction in renal medullary atrophy in mice subjected to unilateral ureteral obstruction and a complete reversal of obesity and diabetes phenotypes in mice fed a constant high-fat diet. Crucially, we discovered that a single formulation combining 2 separate therapies into 1 was able to treat all 4 diseases. These results emphasize the promise of gene therapy for treating diverse age-related ailments and demonstrate the potential of combination gene therapy that may improve health span and longevity by addressing multiple diseases at once.

An enhanced CRISPR repressor for targeted mammalian gene regulation.

The RNA-guided endonuclease Cas9 can be converted into a programmable transcriptional repressor, but inefficiencies in target-gene silencing have limited its utility. Here we describe an improved Cas9 repressor based on the C-terminal fusion of a rationally designed bipartite repressor domain, KRAB-MeCP2, to nuclease-dead Cas9. We demonstrate the system's superiority in silencing coding and noncoding genes, simultaneously repressing a series of target genes, improving the results of single and dual guide RNA library screens, and enabling new architectures of synthetic genetic circuits.

Highly efficient Cas9-mediated transcriptional programming.

The RNA-guided nuclease Cas9 can be reengineered as a programmable transcription factor. However, modest levels of gene activation have limited potential applications. We describe an improved transcriptional regulator obtained through the rational design of a tripartite activator, VP64-p65-Rta (VPR), fused to nuclease-null Cas9. We demonstrate its utility in activating endogenous coding and noncoding genes, targeting several genes simultaneously and stimulating neuronal differentiation of human induced pluripotent stem cells (iPSCs).

Gene Therapy-Mediated Partial Reprogramming Extends Lifespan and Reverses Age-Related Changes in Aged Mice.

Aging is a complex progression of changes best characterized as the chronic dysregulation of cellular processes leading to deteriorated tissue and organ function. Although aging cannot currently be prevented, its impact on life- and healthspan in the elderly can potentially be minimized by interventions that aim to return these cellular processes to optimal function. Recent studies have demonstrated that partial reprogramming using the Yamanaka factors (or a subset; OCT4, SOX2, and KLF4; OSK) can reverse age-related changes in vitro and in vivo. However, it is still unknown whether the Yamanaka factors (or a subset) are capable of extending the lifespan of aged wild-type (WT) mice. In this study, we show that systemically delivered adeno-associated viruses, encoding an inducible OSK system, in 124-week-old male mice extend the median remaining lifespan by 109% over WT controls and enhance several health parameters. Importantly, we observed a significant improvement in frailty scores indicating that we were able to improve the healthspan along with increasing the lifespan. Furthermore, in human keratinocytes expressing exogenous OSK, we observed significant epigenetic markers of age reversal, suggesting a potential reregulation of genetic networks to a younger potentially healthier state. Together, these results may have important implications for the development of partial reprogramming interventions to reverse age-associated diseases in the elderly.

Modular design of artificial tissue homeostasis: robust control through synthetic cellular heterogeneity.

Synthetic biology efforts have largely focused on small engineered gene networks, yet understanding how to integrate multiple synthetic modules and interface them with endogenous pathways remains a challenge. Here we present the design, system integration, and analysis of several large scale synthetic gene circuits for artificial tissue homeostasis. Diabetes therapy represents a possible application for engineered homeostasis, where genetically programmed stem cells maintain a steady population of ß-cells despite continuous turnover. We develop a new iterative process that incorporates modular design principles with hierarchical performance optimization targeted for environments with uncertainty and incomplete information. We employ theoretical analysis and computational simulations of multicellular reaction/diffusion models to design and understand system behavior, and find that certain features often associated with robustness (e.g., multicellular synchronization and noise attenuation) are actually detrimental for tissue homeostasis. We overcome these problems by engineering a new class of genetic modules for 'synthetic cellular heterogeneity' that function to generate beneficial population diversity. We design two such modules (an asynchronous genetic oscillator and a signaling throttle mechanism), demonstrate their capacity for enhancing robust control, and provide guidance for experimental implementation with various computational techniques. We found that designing modules for synthetic heterogeneity can be complex, and in general requires a framework for non-linear and multifactorial analysis. Consequently, we adapt a 'phenotypic sensitivity analysis' method to determine how functional module behaviors combine to achieve optimal system performance. We ultimately combine this analysis with Bayesian network inference to extract critical, causal relationships between a module's biochemical rate-constants, its high level functional behavior in isolation, and its impact on overall system performance once integrated.

Accurate predictions of genetic circuit behavior from part characterization and modular composition.

A long-standing goal of synthetic biology is to rapidly engineer new regulatory circuits from simpler devices. As circuit complexity grows, it becomes increasingly important to guide design with quantitative models, but previous efforts have been hindered by lack of predictive accuracy. To address this, we developed Empirical Quantitative Incremental Prediction (EQuIP), a new method for accurate prediction of genetic regulatory network behavior from detailed characterizations of their components. In EQuIP, precisely calibrated time-series and dosage-response assays are used to construct hybrid phenotypic/mechanistic models of regulatory processes. This hybrid method ensures that model parameters match observable phenomena, using phenotypic formulation where current hypotheses about biological mechanisms do not agree closely with experimental observations. We demonstrate EQuIP's precision at predicting distributions of cell behaviors for six transcriptional cascades and three feed-forward circuits in mammalian cells. Our cascade predictions have only 1.6-fold mean error over a 261-fold mean range of fluorescence variation, owing primarily to calibrated measurements and piecewise-linear models. Predictions for three feed-forward circuits had a 2.0-fold mean error on a 333-fold mean range, further demonstrating that EQuIP can scale to more complex systems. Such accurate predictions will foster reliable forward engineering of complex biological circuits from libraries of standardized devices.

An end-to-end workflow for engineering of biological networks from high-level specifications.

We present a workflow for the design and production of biological networks from high-level program specifications. The workflow is based on a sequence of intermediate models that incrementally translate high-level specifications into DNA samples that implement them. We identify algorithms for translating between adjacent models and implement them as a set of software tools, organized into a four-stage toolchain: Specification, Compilation, Part Assignment, and Assembly. The specification stage begins with a Boolean logic computation specified in the Proto programming language. The compilation stage uses a library of network motifs and cellular platforms, also specified in Proto, to transform the program into an optimized Abstract Genetic Regulatory Network (AGRN) that implements the programmed behavior. The part assignment stage assigns DNA parts to the AGRN, drawing the parts from a database for the target cellular platform, to create a DNA sequence implementing the AGRN. Finally, the assembly stage computes an optimized assembly plan to create the DNA sequence from available part samples, yielding a protocol for producing a sample of engineered plasmids with robotics assistance. Our workflow is the first to automate the production of biological networks from a high-level program specification. Furthermore, the workflow's modular design allows the same program to be realized on different cellular platforms simply by swapping workflow configurations. We validated our workflow by specifying a small-molecule sensor-reporter program and verifying the resulting plasmids in both HEK 293 mammalian cells and in E. coli bacterial cells.