Computational design of self-assembling proteins has long relied on pre-existing structures and sequences, fundamentally limiting control over their structural and functional properties. Recent machine learning-based methods have transformed our ability to design functional small de novo proteins and oligomers, yet methods to design large de novo protein assemblies with structures tailored to specific applications are still underexplored. Here, we develop a generalizable method for designing de novo symmetric protein complexes that incorporate target functional motifs into their structures. We report 34 new protein nanoparticles that form on-target assemblies with cubic point group symmetries. The nanoparticles exhibit a wide variety of backbones that were designed with atom-level accuracy, as evidenced by several cryo-EM and crystal structures that reveal minimal deviations from the design models. We use the method to generate a de novo antigen-tailored nanoparticle vaccine that elicits robust immune responses in mice. These results establish a generalizable approach that can be used to design functional self-assembling protein complexes with structures tailored to specific applications.

Hydrogels are widely used as three-dimensional cell culture systems to understand the impact of cellular mechanotransduction for tissue engineering applications. Photoinitiated thiol-ene click chemistry is a commonly utilized hydrogel crosslinking mechanism that provides spatial and temporal control over hydrogel network formation and resulting mesh size and compressive properties. Despite historically documented efficiency as step-growth reactions, these reactions do not always proceed as predicted. To understand the impact of cell confinement and microenvironmental mechanics on cellular function, thiol-ene network formation must be thoroughly characterized. To this end, the objective of this work was to investigate the crosslinking dynamics to determine hydrogel network formation as assessed via mesh size and mechanical properties using a pentenoate-functionalized hyaluronic acid thiol-ene reaction. Hydrogel parameters including polymer concentration and thiol:-ene crosslinker molar ratio were modulated (4, 6, or 8 polymer weight percent and 0.15:1, 0.5:1, or 1:1 molar ratio of thiol groups to reactive -ene groups) to tune network properties including shear storage modulus and relative mesh size. Molecular Dynamics (MD) simulations were used to simulate the thiol-ene crosslinking reaction and establish a method for predicting thiol-ene reaction efficiency. Lastly, the feasibility of this hydrogel system for in vitro modeling was confirmed via assessment of metabolic activity of encapsulated primary human meniscal cells.

Over the past decade, the integration of microgel-based granular hydrogels in biomedical technologies has experienced substantial growth due to the numerous benefits microgels offer. However, the inability to easily adopt uniform microgel fabrication workflows at scale constitutes a major bottleneck, or in some cases, a barrier-to-entry that stunts further growth of the field. The gold-standard technique for emulsion-based microgel production is through microfluidic droplet-generating devices that produce liquid gel precursor droplets that gel post-production. However, traditional microfluidic workflows often require multiple independent flows and controlled pressure sources, along with a steep learning curve in using microfluidics to achieve uniform droplet sizes reproducibly and repeatedly. This difficulty in adopting microgel fabrication is further compounded by low throughput and the extensive flow rate calibration required when switching to new formulations (e.g., material type, droplet size). In this work, we present a step-emulsion system that bridges the gap by providing a robust and simple setup. We experimentally characterize and evaluate how flow and outlet channel dimension contribute to the generation of uniform droplet populations at specific sizes. With our large dataset consisting of various outlet channel dimensions, we evaluated outlet channel geometrical impacts (height, width, cross-sectional area, aspect-ratio, etc.) on gel precursor droplet size and generation throughput. We demonstrate robust, highly compatible, and repeatably uniform droplet generation from various gel precursor polymer backbones, users with varying microfluidics experience, and a wide viscosity range, including alginate solutions with 650 times the viscosity of water. Furthermore, we confirmed consistent gel precursor droplet generation outcomes driven by a constant flow source (syringe pump) and by direct manual injection as a simple and highly adoptable option for the generation of gel precursor droplets. This platform is ideal for researchers seeking rapid and easy microgel fabrication, regardless of microfluidics experience.

Recombinant protein-based biomaterials offer exciting opportunities in materials design and controlled therapeutic delivery. Though their precursors can be readily synthesized with near-perfect monodispersity and sequence specificity through scalable fermentation processes, recombinant protein materials have yet to achieve the same level of multi-stimuli-responsiveness as their synthetic counterparts. Integrating cutting-edge tools from chemical biology, we autonomously compile topologically specified protein crosslinkers that can be degraded following user-programmable Boolean logic. Covalent step polymerization of these linkers into protein hydrogels yields smart materials whose cargo (e.g., bioactive proteins, cellular therapeutics) can be liberated following bulk degradation in response to user-specified input combinations. Demonstrating the versatility of this approach, we release fluorescent protein mGreenLantern following all 17 possible YES/OR/AND logic outputs in response to a 3-input protease operator set, deliver epidermal growth factor following advanced biocomputation while maintaining native bioactivity, and showcase multiplexed delivery of living cells, all from fully recombinant protein-based hydrogels. Incorporating advanced intelligence into protein biomaterial responsiveness, we anticipate these methods will dramatically expand potential applications in tissue engineering and precision medicine.

Protein-based biomaterials have risen in popularity in recent years owing to their genetic encodability, sequence specificity, monodispersity, and ability to interface with biological systems in comparison with synthetic polymer-based materials. Though naturally derived and minimally engineered proteins have been at the forefront of these efforts, recent advances in computational protein design offer exciting opportunities for next-generation biomaterial development. In this work, we employ de novo protein design methodologies to generate a suite of self-assembling multimeric proteins, whose step-growth heteropolymerization into bulk hydrogels and condensates can be exogenously triggered through small-molecule addition. Our results highlight how changes in programmed multimer valency and their triggered assembly yield materials with varying structures and viscoelasticity. We anticipate that these approaches will prove useful in rapidly generating large libraries of stimuli-responsive biomaterials that are precisely tailored to specific applications in the biosciences and beyond.

The extracellular matrix (ECM) plays a pivotal role in shaping tumor behavior by providing biochemical and biophysical cues to cancer cells. Traditional 2D culture systems fail to recapitulate this complexity, and in vivo systems do not readily allow for interrogation of how individual ECM components influence tumor cell behavior. Here, we introduce a fully synthetic, tunable three-dimensional (3D) hydrogel that mimics a soft tissue tumor microenvironment (TME) to enable mechanistic studies of ECM-tumor interactions. The hydrogel features a proteolytically degradable poly(ethylene glycol) base network functionalized with integrin-binding peptides derived from ECM components collagen I and fibronectin. To model metastatic ECM and further tune the hydrogel, we incorporated a tenascin-C (TNC)-derived peptide. To study the impact of these tunable ECM parameters on cancer cell behavior, we encapsulated Ewing sarcoma (EwS) cells within the hydrogels. EwS is an aggressive bone and soft tissue tumor that commonly metastasizes to lung. Our studies demonstrated matrix-dependent growth and phenotypic variation of EwS cells. Specifically, the TNC peptide drove divergent tumor behaviors and induced cell state changes consistent with alterations induced by the native TNC protein. To facilitate downstream functional assays, the hydrogel incorporates sortase-degradable crosslinkers that enable non-perturbative recovery of encapsulated cells. This platform provides a reductionist and reproducible model for studying the ECM's role in cancer cell biology while addressing long-standing challenges in polymeric hydrogel degradation and cell retrieval. Collectively, this work establishes a biomaterials-based framework to dissect EwS tumor-ECM interactions in a controllable 3D microenvironment. STATEMENT OF SIGNIFICANCE: Engineered biomaterials to model Ewing sarcoma (EwS) have been previously employed to study metastasis to the bone. While important efforts, platforms to study EwS metastasis in lung - the most common site of metastasis - have not been developed. Here, we introduce a user-programmable biomaterial designed to mimic the environment of soft tissue metastases. The platform features several attributes: 1) it is mechanically matched to lung tissue; 2) it is readily functionalized with extracellular matrix protein-derived peptides (e.g., Tenascin-C); 3) encapsulated cells can be retrieved in a "biologically invisible" manner via sortase-mediated gel degradation, enabling expanded downstream analysis. This platform provides a powerful, reproducible tool to dissect tumor behavior and identify new targets for cancer therapy.

Stimulus-responsive materials have enabled advanced applications in biosensing, tissue engineering and therapeutic delivery. Although controlled molecular topology has been demonstrated as an effective route toward creating materials that respond to prespecified input combinations, prior efforts suffer from a reliance on complicated and low-yielding multistep organic syntheses that dramatically limit their utility. Harnessing the power of recombinant expression, we integrate emerging chemical biology tools to create topologically specified protein cargos that can be site-specifically tethered to and conditionally released from biomaterials following user-programmable Boolean logic. Critically, construct topology is autonomously compiled during expression through spontaneous intramolecular ligations, enabling direct and scalable synthesis of advanced operators. Using this framework, we specify protein release from biomaterials following all 17 possible YES/OR/AND logic outputs from input combinations of three orthogonal protease actuators, multiplexed delivery of three distinct biomacromolecules from hydrogels, five-input-based conditional cargo liberation and logically defined protein localization on or within living mammalian cells.

3D printing has accelerated tissue engineering by enabling rapid fabrication of bioprinted tissues from a variety of soft biomaterials. Yet, an ongoing challenge is that for many bioprinting technologies, the materials (bioinks) need to be printed “stiff” (i.e., G′ > 15 kPa) so that the fabricated tissue constructs retain high resolution and shape fidelity. Conversely, softer materials tend to generally be more supportive of cellular phenotype and function. To bridge this gap, we sought to develop a hydrogel system that would expand bioprinting access to softer materials, while retaining the resolution of fabricated spatial features. We developed a photopolymerizable copolymer hydrogel system consisting of nondegradable synthetic and proteolytically degradable natural polymers. Varying the overall polymer content, as well as the ratio between the poly(ethylene glycol) and gelatin species, we generated a library of lithographically printable hydrogel formulations with differing initial stiffnesses that could be further variably softened following enzymatic treatment using collagenase. Varying the copolymer composition and overall concentration resulted in the creation of gels whose initial stiffness ranged from 82 to 2 kPa and could be subsequently softened up to 20-fold upon enzymatic treatment. When 3D-printed via digital light processing (DLP), softened gels maintained higher structural integrity than those with matched initial stiffness. Softened gels supported greater endothelial cell perfusion-based seeding compared to those untreated while maintaining high cell viability. Our material system presents a simple solution to the ongoing challenge of 3D-printing soft materials with high resolution. In future studies, we will develop post-print softening materials with bio-invisible stimuli to expand applications to in vivo softening of biomaterial tissue mimics. 3D-printing has become popular in tissue engineering applications, but printing complex, organ-like structures with soft materials remains challenging. We created a material that can hold patterned shapes and small printed structures using a post-print softening technique with a degrading enzyme. We found that different formulations of this hydrogel material offer varying stiffness levels (G′ = 2 kPa–82 kPa) and can soften up to 20-fold with enzymatic treatment. Notably, this material retains the structure of 3D-printed open channels even after significant softening, and cells respond well when seeded in these channels. This demonstrates the promise of post-print softening to create soft 3D-printed materials.

Enzymatic reactions offer many advantages for hydrogel synthesis and modification, due to their gentle reaction conditions, biocompatibility, and diversity of substrates. In this review, we examine the current body of literature through databases such as Google Scholar, PubMed, and Web of Science. Various enzyme classes have been utilized for hydrogel assembly and disassembly, including transglutaminases, oxidoreductases, transpeptidases, and proteinases. The enzymatic substrates can be readily included in peptide precursors and/or appended onto synthetic polymers. We discuss the benefits and limitations of each system, with a focus on ease of use/synthesis, accessibility, and financial considerations. Enzymes are frequently utilized to modify both natural and synthetic biomaterials. For developing more advanced, stimuli-responsive platforms, “biologically invisible” enzymes such as sortases should be leveraged to not interfere with native processes and/or the mammalian proteome. Enzymes, proteins that act as biological catalysts, are an important tool for making and breaking down hydrogels, or water-swollen polymeric networks, for various biomedical applications. In particular, these techniques have seen great usage for modeling the tissue environment for lab-based assays.

Integrin α5β1 is crucial for cell attachment and migration in development and tissue regeneration, and α5β1 binding proteins can have considerable utility in regenerative medicine and next-generation therapeutics. We use computational protein design to create de novo α5β1-specific modulating miniprotein binders, called NeoNectins, that bind to and stabilize the open state of α5β1. When immobilized onto titanium surfaces and throughout 3D hydrogels, the NeoNectins outperform native fibronectin (FN) and RGD peptides in enhancing cell attachment and spreading, and NeoNectin-grafted titanium implants outperformed FN- and RGD-grafted implants in animal models in promoting tissue integration and bone growth. NeoNectins should be broadly applicable for tissue engineering and biomedicine.

Hydrogels are an important class of biomaterials that permit cells to be cultured and studied within engineered microenvironments of user-defined physical and chemical properties. Though conventional 3D extrusion and stereolithographic (SLA) printing readily enable homogeneous and multimaterial hydrogels to be formed with specific macroscopic geometries, strategies that further afford spatiotemporal customization of the underlying gel physicochemistry in a non-discrete manner would be profoundly useful toward recapitulating the complexity of native tissue in vitro. Here, we demonstrate that grayscale control over local biomaterial biochemistry and mechanics can be rapidly achieved across large constructs using an inexpensive (~$300) and commercially available liquid crystal display (LCD)-based printer. Template grayscale images are first processed into a “height-extruded” 3D object, which is then printed on a standard LCD printer with an immobile build head. As the local height of the 3D object corresponds to the final light dosage delivered at the corresponding xy -coordinate, this method provides a route toward spatially specifying the extent of various dosage-dependent and biomaterial, forming/modifying photochemistries. Demonstrating the utility of this approach, we photopattern the grayscale polymerization of poly(ethylene glycol) (PEG) diacrylate gels, biochemical functionalization of agarose- and PEG-based gels via oxime ligation, and the controlled 2D adhesion and 3D growth of cells in response to a de novo -designed α5β1-modulating protein via thiol-norbornene click chemistry. Owing to the method's low cost, simple implementation, and high compatibility with many biomaterial photochemistries, we expect this strategy will prove useful toward fundamental biological studies and functional tissue engineering alike.

Free-standing tissue structures tethered between pillars are powerful mechanobiology tools for studying cell contraction. To model interfaces ubiquitous in natural tissues and upgrade existing single-region suspended constructs, we developed Suspended Tissue Open Microfluidic Patterning (STOMP), a method to create multi-regional suspended tissues. STOMP uses open microfluidics and capillary pinning to pattern subregions within free-standing tissues, facilitating the study of complex tissue interfaces, such as diseased-healthy boundaries (e.g., fibrotic-healthy) and tissue-type interfaces (e.g., bone-ligament). We observed altered contractile dynamics in fibrotic-healthy engineered heart tissues compared to single-region tissues and differing contractility in bone-ligament enthesis constructs compared to single-tissue periodontal ligament models. STOMP is a versatile platform - surface tension-driven patterning removes material requirements common with other patterning methods (e.g., shear-thinning, photopolymerizable) allowing tissue generation in multiple geometries with native extracellular matrices and advanced four-dimensional (4D) materials. STOMP combines the contractile functionality of suspended tissues with precise patterning, enabling dynamic and spatially controlled studies.

Colorectal cancer (CRC) studies in vitro have been conducted almost exclusively on 2D cell monolayers or suspension spheroid cultures. Though these platforms have shed light on many important aspects of CRC biology, they fail to recapitulate essential cell-matrix interactions that often define in vivo function. Toward filling this knowledge gap, synthetic hydrogel biomaterials with user-programmable matrix mechanics and biochemistry have gained popularity for culturing cells in a more physiologically relevant 3D context. Here, using a poly(ethylene glycol)-based hydrogel model, we systematically assess the role of matrix stiffness and fibronectin-derived RGDS adhesive peptide presentation on CRC colony morphology and proliferation. Highlighting platform generalizability, we demonstrate that these hydrogels can support the viability and promote spontaneous spheroid or multicellular aggregate formation of six CRC cell lines that are commonly utilized in biomedical research. These gels are engineered to be fully degradable via a "biologically invisible" sortase-mediated reaction, enabling the triggered recovery of single cells and spheroids for downstream analysis. Using these platforms, we establish that substrate mechanics play a significant role in colony growth: soft conditions (∼300 Pa) encourage robust colony formation, whereas stiffer (∼2 kPa) gels severely restrict growth. Tuning the RGDS concentration did not affect the colony morphology. Additionally, we observe that epidermal growth factor receptor (EGFR) signaling in Caco-2 cells is influenced by adhesion ligand identity─whether the adhesion peptide was derived from collagen type I (DGEA) or fibronectin (RGDS)─with DGEA yielding a marked decrease in the level of downstream protein kinase phosphorylation. Taken together, this study introduces a versatile method to culture and probe CRC cell-matrix interactions within engineered 3D biomaterials.

Stimuli‐responsive biomaterials hold great promise in controlled therapeutic delivery, tissue engineering, and biosensing applications. Recently, molecular assembly via autonomous compilation has been employed to create topologically specified protein cargos that can be site‐specifically tethered to and conditionally released from biomaterials following user‐programmable Boolean logic. Prior implementation has been confined to simple fluorescent protein outputs and model protease inputs. In this manuscript, we extend the applicability of this framework by assembling all 7 unique logical operations emanating from a YES/OR/AND 3‐input operator set to deliver bioactive proteins spanning diverse categories: growth factors (epidermal growth factor), model enzymes (β‐lactamase, NanoLuciferase, and thioredoxin A), therapeutic nanobodies (anti‐human epidermal growth factor receptor 2), de novo‐engineered cytokines (Neoleukin), and fluorescent proteins (mGreenLantern). In so doing, we demonstrate programmable biomacromolecule release from material anchors in response to precise combinations of three orthogonal protease actuators while maintaining native bioactivity. Through inclusion of a photocleavable protein motif, we further establish that visible light can be employed as an additional input in specifying logic‐based protein release. We anticipate these methods will powerfully expand opportunities for targeted therapeutic delivery and beyond.

Cardiomyocyte hypocontractility underlies inherited dilated cardiomyopathy (DCM). Yet, whether fibroblasts modify DCM phenotypes remains unclear despite their regulation of fibrosis, which strongly predicts disease severity. Expression of a hypocontractility-linked sarcomeric variant in mice triggered cardiac fibroblast expansion from the de novo formation of hyperproliferative mechanosensitized fibroblast states, which occurred prior to eccentric myocyte remodeling. Initially, this fibroblast response reorganized fibrillar collagen and stiffened the myocardium, albeit without depositing fibrotic tissue. These adaptations coincided with heightened matrix-integrin receptor interactions and diastolic tension sensation at focal adhesions within fibroblasts. Targeted p38 deletion arrested these cardiac fibroblast responses in DCM mice, which prevented cardiomyocyte remodeling and improved contractility. p38-mediated fibroblast responses were essential regulators of DCM severity, marking a potential cellular target for therapeutic intervention.

Hydrogel biomaterials offer great promise for three-dimensional cell culture and therapeutic delivery. Despite many successes, challenges persist in that gels formed from natural proteins are only marginally tunable whereas those derived from synthetic polymers lack intrinsic bioinstructivity. Toward the creation of biomaterials with both excellent biocompatibility and customizability, recombinant protein-based hydrogels have emerged as molecularly defined and user-programmable platforms that mimic the proteinaceous nature of the extracellular matrix. Here, we introduce PhoCoil, a dynamically tunable recombinant hydrogel formed from a single protein component with unique multistimuli responsiveness. Physical cross-linking through coiled-coil interactions promotes rapid shear-thinning and self-healing behavior, rendering the gel injectable, whereas an included photodegradable motif affords on-demand network dissolution via visible light. PhoCoil gel photodegradation can be spatiotemporally and lithographically controlled in a dose-dependent manner, through complex tissue, and without harm to encapsulated cells. We anticipate that PhoCoil will further enable applications in tissue engineering and regenerative medicine.

Protein-based biomaterials are growing in popularity for biomedical applications, in part owing to their innate ability to interface with biological systems. These materials, in the form of fibres, nanoparticles and hydrogels, have shown promise as drug delivery vehicles, tissue scaffolds and vaccines. Moreover, the explosion of protein engineering tools and the inception of de novo protein design have transformed our ability to explore new protein structures, enabling the creation of novel materials with diverse properties and furthering their customization for various applications. In this Perspective, we explore the coming of age of protein engineering technologies and their impact on biomaterials. Starting with naturally sourced materials, we highlight common protein building blocks and fabrication methods, as well as recent applications of each. We subsequently explore rationally designed materials and conclude by discussing the potential impacts that de novo design will have on the biomaterials field. Protein-based biomaterials are becoming increasingly prevalent in biomedical applications that treat and prevent disease. This Perspective examines the evolution of techniques used to build and design these protein-based biomaterials, including fibres, nanoparticles and hydrogels, and explores how the field will be impacted by the newest tools in de novo protein design.

Though recombinant protein therapeutics hold great potential in treating many diseases, their intravenous delivery introduces challenges with off-target effects and short circulation half-lives. Injectable biomaterial depots have proven useful in confining therapeutic administration to specific bodily locations but have faced difficulties in simultaneously controlling drug release, network mechanics, and functionalization. Toward addressing these limitations, this work introduces the first recombinant protein-based interpenetrating polymer network (IPN), which we exploit for injectable therapeutic deposition. Each of the self-sorting telechelic biopolymer networks is comprised of an intrinsically disordered XTEN protein midblock differentially flanked with one of two orthogonally self-assembling coil domains that enable rapid shear-thinning and self-healing responsiveness in biomaterials with tunable viscoelasticity. Exploiting the orthogonal and genetically encoded click-like SpyLigation/SnoopLigation chemistries to independently tether proteins-of-interest to each underlying network, we demonstrate that fluorescent proteins and growth factors (rhIGF-1, rhEGF) can be released in a controlled fashion from materials with tunable viscoelasticity while retaining high bioactivity following network dissolution. Such recombinant IPN biomaterials offer exciting opportunities for next-generation biotherapeutic delivery.

Human engineered tissues hold great promise for therapeutic tissue regeneration and repair. Yet, development of these technologies often stalls at the stage of in vivo studies due to the complexity of engineered tissue formulations, which are often composed of diverse cell populations and material elements, along with the tedious nature of in vivo experiments. We introduce a "plug and play" platform called parallelized host apposition for screening tissues in vivo (PHAST). PHAST enables parallelized in vivo testing of 43 three-dimensional microtissues in a single 3D-printed device. Using PHAST, we screen microtissue formations with varying cellular and material components and identify formulations that support vascular graft-host inosculation and engineered liver tissue function in vivo. Our studies reveal that the cellular population(s) that should be included in engineered tissues for optimal in vivo performance is material dependent. PHAST could thus accelerate development of human tissue therapies for clinical regeneration and repair.

Self-assembling protein nanoparticles are being increasingly utilized in the design of next-generation vaccines due to their ability to induce antibody responses of superior magnitude, breadth, and durability. Computational protein design offers a route to nanoparticle scaffolds with structural and biochemical features tailored to specific vaccine applications. Although strategies for designing self-assembling proteins have been established, the recent development of powerful machine learning (ML)-based tools for protein structure prediction and design provides an opportunity to overcome several of their limitations. Here, we leveraged these tools to develop a generalizable method for designing self-assembling proteins starting from AlphaFold2 predictions of oligomeric protein building blocks. We used the method to generate six 60-subunit protein nanoparticles with icosahedral symmetry, and single-particle cryoelectron microscopy reconstructions of three of them revealed that they were designed with atomic-level accuracy. To transform one of these nanoparticles into a functional immunogen, we reoriented its termini through circular permutation, added a genetically encoded oligomannose-type glycan, and displayed a stabilized trimeric variant of the influenza hemagglutinin receptor-binding domain through a rigid de novo linker. The resultant immunogen elicited potent receptor-blocking and neutralizing antibody responses in mice. Our results demonstrate the practical utility of ML-based protein modeling tools in the design of nanoparticle vaccines. More broadly, by eliminating the requirement for experimentally determined structures of protein building blocks, our method dramatically expands the number of starting points available for designing self-assembling proteins.