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Synthetic biology is driving a new era of medicine through the genetic programming of living cells 1 , 2 . This transformative approach allows for the creation of engineered systems that intelligently sense and respond to diverse environments, ultimately adding specificity and efficacy that extends beyond the capabilities of molecular-based therapeutics 3 – 6 . One particular area of focus has been the engineering of bacteria as therapeutic delivery systems to selectively release therapeutic payloads in vivo 7 – 11 . Here we engineered a non-pathogenic Escherichia coli strain to specifically lyse within the tumor microenvironment and release an encoded nanobody antagonist of CD47 (CD47nb) 12 , an anti-phagocytic receptor that is commonly overexpressed in several human cancer types 13 , 14 . We show that delivery of CD47nb by tumor-colonizing bacteria increases activation of tumor-infiltrating T cells, stimulates rapid tumor regression, prevents metastasis and leads to long-term survival in a syngeneic tumor model in mice. Moreover, we report that local injection of CD47nb-expressing bacteria stimulates systemic tumor-antigen-specific immune responses that reduce the growth of untreated tumors, providing proof-of-concept for an abscopal effect induced by an engineered bacterial immunotherapy. Thus, engineered bacteria may be used for safe and local delivery of immunotherapeutic payloads leading to systemic antitumor immunity. Local release of an anti-CD47 nanobody from an engineered non-pathogenic Escherichia coli strain is safe and enhances activation of tumor-infiltrating T cells, slowing tumor growth in mice.

Chimeric antigen receptor (CAR)-T-cell therapy for solid tumors is limited due to heterogeneous target antigen expression and outgrowth of tumors lacking the antigen targeted by CAR-T cells directed against single antigens. Here, we developed a bicistronic construct to drive expression of a CAR specific for EGFRvIII, a glioblastoma-specific tumor antigen, and a bispecific T-cell engager (BiTE) against EGFR, an antigen frequently overexpressed in glioblastoma but also expressed in normal tissues. CART.BiTE cells secreted EGFR-specific BiTEs that redirect CAR-T cells and recruit untransduced bystander T cells against wild-type EGFR. EGFRvIII-specific CAR-T cells were unable to completely treat tumors with heterogenous EGFRvIII expression, leading to outgrowth of EGFRvIII-negative, EGFR-positive glioblastoma. However, CART.BiTE cells eliminated heterogenous tumors in mouse models of glioblastoma. BiTE-EGFR was locally effective but was not detected systemically after intracranial delivery of CART.BiTE cells. Unlike EGFR-specific CAR-T cells, CART.BiTE cells did not result in toxicity against human skin grafts in vivo. BiTE-secreting CAR-T cells overcome antigen escape from EGFRvIII-targeted therapy for glioblastoma.

Genetic encoding of noncanonical amino acid (ncAA) for site-specific protein modification has been widely applied for many biological and therapeutic applications. To efficiently prepare homogeneous protein multiconjugates, we design two encodable noncanonical amino acids (ncAAs), 4-(6-(3-azidopropyl)-s-tetrazin-3-yl) phenylalanine (pTAF) and 3-(6-(3-azidopropyl)-s-tetrazin-3-yl) phenylalanine (mTAF), containing mutually orthogonal and bioorthogonal azide and tetrazine reaction handles. Recombinant proteins and antibody fragments containing the TAFs can easily be functionalized in one-pot reactions with combinations of commercially available fluorophores, radioisotopes, PEGs, and drugs in a plug-and-play manner to afford protein dual conjugates to assess combinations of tumor diagnosis, image-guided surgery, and targeted therapy in mouse models. Furthermore, we demonstrate that simultaneously incorporating mTAF and a ketone-containing ncAA into one protein via two non-sense codons allows preparation of a site-specific protein triconjugate. Our results demonstrate that TAFs are doubly bio-orthogonal handles for efficient and scalable preparation of homogeneous protein multiconjugates. Site-specific protein multi-conjugates are important for both scientific and translational research. Here, the authors genetically encode unnatural amino acids which contain both tetrazine and azide, and use the doubly bio-orthogonal handles to generate bi- and tri-conjugate proteins in high yields.

Osteoarthritis (OA), primarily characterized by articular cartilage destruction, is the most common form of age-related degenerative whole-joint disease. No disease-modifying treatments for OA are currently available. Although OA is primarily characterized by cartilage destruction, our understanding of the processes controlling OA progression is poor. Here, we report the association of OA with increased levels of osteoclast-associated receptor (OSCAR), an immunoglobulin-like collagen-recognition receptor. In mice, OSCAR deletion abrogates OA manifestations, such as articular cartilage destruction, subchondral bone sclerosis, and hyaline cartilage loss. These effects are a result of decreased chondrocyte apoptosis, which is caused by the tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) in induced OA. Treatments with human OSCAR-Fc fusion protein attenuates OA pathogenesis caused by experimental OA. Thus, this work highlights the function of OSCAR as a catabolic regulator of OA pathogenesis, indicating that OSCAR blockade is a potential therapy for OA. Osteoarthritis (OA) is associated with cartilage disruption, but the underlying mechanisms remain unclear. Here, the authors show that expression of osteoclast-associated receptor (OSCAR) is associated with OA, that its genetic ablation or targeting with OSCAR-Fc fusion protein ameliorates OA in mice by decreasing chondrocyte apoptosis.

Antibody engineering technologies face increasing demands for speed, reliability and scale. We develop CeVICA, a cell-free nanobody engineering platform that uses ribosome display for in vitro selection of nanobodies from a library of 10 11 randomized sequences. We apply CeVICA to engineer nanobodies against the Receptor Binding Domain (RBD) of SARS-CoV-2 spike protein and identify >800 binder families using a computational pipeline based on CDR-directed clustering. Among 38 experimentally-tested families, 30 are true RBD binders and 11 inhibit SARS-CoV-2 pseudotyped virus infection. Affinity maturation and multivalency engineering increase nanobody binding affinity and yield a virus neutralizer with picomolar IC50. Furthermore, the capability of CeVICA for comprehensive binder prediction allows us to validate the fitness of our nanobody library. CeVICA offers an integrated solution for rapid generation of divergent synthetic nanobodies with tunable affinities in vitro and may serve as the basis for automated and highly parallel nanobody engineering. Faster, higher throughput antibody engineering methods are needed. Here the authors present CeVICA, a cell-free nanobody engineering platform using ribosome display and computational clustering analysis for in vitro selection; they use this to develop nanobodies against the RBD of SARS-CoV-2 spike protein.

While various GPCRs, including US28, display constitutive, ligand-independent activity, it remains to be established whether ligand-dependent and -independent active conformations differ and can be selectively modulated. Previously, the agonist-bound conformation of US28 was stabilized and its structure was solved using the anti-US28 nanobody Nb7. Here we report the recognition of the constitutively active, apo-conformation of US28 by another nanobody VUN103. While the Nb7 intrabody selectively inhibits ligand-induced signaling, the VUN103 intrabody blocks constitutive signaling, indicating the existence of distinct US28 conformational states. By displacing Gα q protein, VUN103 prevents US28 signaling and reduces tumor spheroids growth. Overall, nanobodies specific for distinct GPCR conformational states, i.e. apo- and agonist-bound, can selectively target and discern functional consequences of ligand-dependent versus independent signaling. Various GPCRs display constitutive ligand-independent activity, but it remains unclear whether ligand-dependent and -independent conformations differ. Here the authors demonstrate the recognition and blocking of G protein recruitment of either the ligand-bound active, or the constitutively active apo-conformation of the viral GPCR US28 by different nanobodies that target similar intracellular loops of the receptor.

Single-chain variable fragments (scFvs), composed of variable domains of heavy and light chains of an antibody joined by a linker, share antigen binding capacity with their parental antibody. Due to intrinsically low solubility and stability, only two Escherichia coli -produced scFvs have been approved for therapy. Here we report that a 33-residue peptide, termed P17 tag, increases the solubility of multiple scFvs produced in Escherichia coli SHuffle strain by up to 11.6 fold. Hydrophilic sequence, especially charged residues, but not the predicted α-helical secondary structure of P17 tag, contribute to the solubility enhancement. Notably, the P17 tag elevates the thermostability of scFv as efficiently as intra-domain disulfide bonds. Moreover, a P17-tagged scFv targeting hepatitis B virus surface proteins shows over two-fold higher antigen-binding affinity and virus-neutralizing activity than the untagged version. These data strongly suggest a type I intramolecular chaperone-like activity of the P17 tag. Hence, the P17 tag could benefit the research, production, and application of scFv. Low solubility and stability of Escherichia coli produced single chain variable fragments (scFvs) restrict their applications. Here the authors report a 33-residue peptide tag which simultaneously increases the solubility and thermostability of multiple scFvs produced in Escherichia coli SHuffle strain.

Numerous monoclonal antibodies have been developed successfully for the treatment of various diseases. Nevertheless, the development of biotherapeutic antibodies is complex, expensive, and time-consuming, and to facilitate this process, careful structural analysis beyond the antibody binding site is required to develop a more efficacious antibody. In this work, we focused on protein antigens, since they induce the largest antibody changes, and provide interesting cases to compare and contrast. The structures of 15 anti-protein antibodies were analysed to compare the antigen-bound/unbound forms. Surprisingly, three different classes of binding-induced changes were identified. In class (B1), the antigen binding fragment distorted significantly, and we found changes in the loop region of the heavy chain’s constant domain; this corresponds well with expected allosteric movements. In class (B2), we found changes in the same loop region without the overall distortion. In class (B3), these changes did not present, and only local changes at the complementarity determining regions were found. Consequently, structural analysis of antibodies is crucial for therapeutic development. Careful evaluation of allosteric movements must be undertaken to develop better effector responses, especially during the transformation of these antibodies from small fragments at the discovery stage to full antibodies at the subsequent development stages.

The cancer “omics” reveal many clinically relevant alterations that are transforming the molecular characterization of glioblastomas. However, many of these findings are not yet translated into clinical practice due, in part, to the lack of non-invasive biomarkers and the limitations imposed by the blood–brain barrier. Nanobodies, camelid single-domain antibody fragments, emerge as a promising tool for immunotargeted applications for diagnosing and treating glioblastomas. Performing agnostic bioinformatic analysis from glioblastoma patient datasets, we identified ATP Binding Cassette subfamily C member 3 (ABCC3) as a suitable target for immunotargeted applications. The expression of ABCC3 is associated with poor survival and impaired response to temozolomide. Importantly, high expression of ABCC3 is restricted to glioblastoma, with negligible levels in healthy brain tissue, and further correlates with tumor grade and stemness markers. We identified three immunogenic epitopes of ABCC3 which were used to isolate nanobodies from a glioblastoma-specific phage-display nanobody library. Two nanobodies targeting ABCC3 (NbA42 and NbA213) were further characterized and demonstrated in vivo selective recognition of ABCC3 in glioblastoma xenograft mouse models upon systemic administration. We designate NbA42 and NbA213 as new candidates to implement immunotargeted applications guiding a more personalized and precise diagnosis, monitoring, and treatment of glioblastoma patients.

Stability studies are vital in biologics development, guiding formulation, packaging, and shelf life determination. Traditionally, predicting long-term stability based on short-term data has been challenging due to the complex behavior of biologics. However, recently have been demonstrated that by using simple kinetics and the Arrhenius equation, it is possible to achieve accurate long-term stability predictions for various quality attributes, including protein aggregates. This study focuses on effective modeling of aggregate predictions for diverse protein modalities, such as IgG1, IgG2, Bispecific IgG, Fc fusion, scFv, bivalent nanobodies, and DARPins, using a first-order kinetic model. Notably, findings highlight the significance of temperature selection in stability studies, enabling the identification of dominant degradation processes. Additionally, simplicity of the first-order kinetic model enhances reliability by reducing the number of parameters and samples required. The model’s effectiveness was further validated across various protein formats, beyond IgG, emphasizing its broad applicability and reliability. Compared to linear extrapolation, the kinetic model provided more precise and accurate stability estimates, even with limited data points. These findings highlight the benefits of using kinetic modeling with optimal temperature selection to predict protein aggregate stability and other quality attributes, aiding biologics development and shelf-life determination.