Ultra-high throughput mapping of genetic design space.

Massively parallel genetic screens have been used to map sequence-to-function relationships for a variety of genetic elements. However, because these approaches only interrogate short sequences, it remains challenging to perform high throughput (HT) assays on constructs containing combinations of sequence elements arranged across multi-kb length scales. Overcoming this barrier could accelerate synthetic biology; by screening diverse gene circuit designs, "composition-to-function" mappings could be created that reveal genetic part composability rules and enable rapid identification of behavior-optimized variants. Here, we introduce CLASSIC, a generalizable genetic screening platform that combines long- and short-read next-generation sequencing (NGS) modalities to quantitatively assess pooled libraries of DNA constructs of arbitrary length. We show that CLASSIC can measure expression profiles of >10 5 drug-inducible gene circuit designs (ranging from 6-9 kb) in a single experiment in human cells. Using statistical inference and machine learning (ML) approaches, we demonstrate that data obtained with CLASSIC enables predictive modeling of an entire circuit design landscape, offering critical insight into underlying design principles. Our work shows that by expanding the throughput and understanding gained with each design-build-test-learn (DBTL) cycle, CLASSIC dramatically augments the pace and scale of synthetic biology and establishes an experimental basis for data-driven design of complex genetic systems.

The Least Mating Pathway: Synthetically Refactoring a Familiar Signaling System for New Applications.

Synthetic refactoring makes naturally occurring regulatory systems more amenable to manipulation by removing or recoding their natural genetic complexity. Shaw et al. apply this technique to the yeast mating response pathway, creating a simplified, highly engineerable signaling module that can be used to construct precisely optimized, application-specific GPCR biosensors.

Hyaluronan Hydrogels for a Biomimetic Spongiosa Layer of Tissue Engineered Heart Valve Scaffolds.

Advanced tissue engineered heart valves must be constructed from multiple materials to better mimic the heterogeneity found in the native valve. The trilayered structure of aortic valves provides the ability to open and close consistently over a full human lifetime, with each layer performing specific mechanical functions. The middle spongiosa layer consists primarily of proteoglycans and glycosaminoglycans, providing lubrication and dampening functions as the valve leaflet flexes open and closed. In this study, hyaluronan hydrogels were tuned to perform the mechanical functions of the spongiosa layer, provide a biomimetic scaffold in which valve cells were encapsulated in 3D for tissue engineering applications, and gain insight into how valve cells maintain hyaluronan homeostasis within heart valves. Expression of the HAS1 isoform of hyaluronan synthase was significantly higher in hyaluronan hydrogels compared to blank-slate poly(ethylene glycol) diacrylate (PEGDA) hydrogels. Hyaluronidase and matrix metalloproteinase enzyme activity was similar between hyaluronan and PEGDA hydrogels, even though these scaffold materials were each specifically susceptible to degradation by different enzyme types. KIAA1199 was expressed by valve cells and may play a role in the regulation of hyaluronan in heart valves. Cross-linked hyaluronan hydrogels maintained healthy phenotype of valve cells in 3D culture and were tuned to approximate the mechanical properties of the valve spongiosa layer. Therefore, hyaluronan can be used as an appropriate material for the spongiosa layer of a proposed laminate tissue engineered heart valve scaffold.

3-Dimensional spatially organized PEG-based hydrogels for an aortic valve co-culture model.

Physiologically relevant in vitro models are needed to study disease progression and to develop and screen potential therapeutic interventions for disease. Heart valve disease, in particular, has no early intervention or non-invasive treatment because there is a lack of understanding the cellular mechanisms which lead to disease. Here, we establish a novel, customizable synthetic hydrogel platform that can be used to study cell-cell interactions and the factors which contribute to valve disease. Spatially localized cell adhesive ligands bound in the scaffold promote cell growth and organization of valve interstitial cells and valve endothelial cells in 3D co-culture. Both cell types maintained phenotypes, homeostatic functions, and produced zonally localized extracellular matrix. This model extends the capabilities of in vitro research by providing a platform to perform direct contact co-culture with cells in their physiologically relevant spatial arrangement.