Biology subjects

Lajoie, M. J.

Publications and source records attributed to Lajoie, M. J..

8 recordsLinked to original sources

bioRxiv2026

A Dynamically Regulated Designed IL-2 for Tumor-localized Signaling

Cytokines mediate cell-cell communication to coordinate immune responses and hold clinical promise as immunotherapies. While natural cytokines are exquisitely regulated by immune cells, engineered cytokines have not yet matched this sophisticated regulation, limiting clinical efficacy and safety. IL-2 is an important cytokine involved in antitumor response, but its production is disrupted in the immune-suppressive tumor microenvironment. Here we designed a regulated IL-2 module, OUTSMART designed IL-2 (dIL-2), that functions robustly in solid tumors and reduces systemic activity that could trigger toxicity: we computationally redesigned IL-2 to have a novel topology that increases stability, preserves native IL-2R{beta}{gamma} interfaces, ablates IL-2R binding, and delivers IL-2 signaling to CD8+ immune-effector cells. This designed cytokine is genetically regulated by a T cell activation-responsive promoter, allowing dynamic production from chimeric antigen receptor (CAR) T cells. Like wild type IL-2, OUTSMART dIL-2 drives T cell proliferation and enhances effector function. Unlike wild type IL-2, it preferentially stimulates CD8+ T cells and Natural Killer (NK) cells, avoids T regulatory cells, and stimulates CAR-T proliferation while preserving stemness, achieving durable tumor elimination in two solid tumor animal models. These design principles can be applied to create other dynamically-regulated cytokine systems that address mechanisms of complex disease.

synthetic biology↗

bioRxiv2026

A Rationally Designed Transgene Drives CAR T Functional Persistence and Durable Regression of Solid Tumors

The eradication of solid tumors by chimeric antigen receptor (CAR) T cells requires dynamic therapies capable of outlasting an immune suppressive tumor microenvironment (TME). However, biological barriers--including rapid exhaustion, poor expansion, and loss of stem-like memory--quickly neutralize these therapies. Because single-technology interventions often introduce unacceptable tradeoffs between efficacy and safety, durable remission demands a paradigm where multiple engineered solutions work in concert. To holistically address these mechanisms, we rationally designed a single-vector transgene that intrinsically drives CAR T functional persistence. The platform integrates four synergistic technologies: a high-avidity mesothelin (MSLN)-targeting CAR optimized to resist shed decoy antigens, a T-cell activation-responsive promoter (OUTLAST OP1) resisting exhaustion, a CD8-targeted designed IL-2 cytokine (OUTSMART dIL-2) driving intratumoral CAR-T expansion, and an EGFRopt safety switch. In lung and ovarian cancer models, this rational integration was required to drive antigen-dependent T cell expansion and eradicate established tumors at extremely low CAR T doses. Furthermore, engineered cells established a self-renewing pool of stem-like memory T cells capable of rejecting tumor rechallenge months later. Ultimately, this work demonstrates that intrinsic T cell dysfunction and extrinsic tumor-derived barriers can be simultaneously overcome by integrating synergistic technologies.

synthetic biology↗

bioRxiv2026

Protein design to broadly reprogram engineered T cell function

The efficacy of engineered T cell therapies in solid tumors remains limited by T cell dysfunction, driven by complex processes that cannot be easily manipulated via genetic knockouts or overexpression of individual genes. Protein design can create new biological functions that can rewire these consequential cell fate decisions. Here, we introduce OUTLAST Regulators, designed proteins that reprogram critical T cell signaling pathways to enhance functional persistence. These proteins are capable of regulating diverse groups of proteins such as the NR4A family of pro-exhaustion transcription factors, E3 ligases Cbl-b and c-Cbl, and SOCS family proteins. Our designs markedly improve CAR-T and TCR-T performance in vitro and in vivo in stringent solid tumor preclinical models. OUTLAST Regulators are implemented as compact genetic modules compatible with standard viral vectors and cell therapy manufacturing processes, creating a powerful platform for programming new functions into enhanced cell and gene therapies.

synthetic biology↗

bioRxiv2022

Safety switch optimization enhances antibody-mediated elimination of CAR T cells

Activation of a conditional safety switch has the potential to reverse serious toxicities arising from the administration of engineered cellular therapies, including chimeric antigen receptor (CAR) T cells. The functionally inert, non-immunogenic cell surface marker derived from human epidermal growth factor receptor (EGFRt) is a promising safety switch that has been used in multiple clinical constructs and can be targeted by cetuximab, a clinically available monoclonal antibody. However, this approach requires high and persistent cell surface expression of EGFRt to ensure that antibody mediated depletion of engineered cells is rapid and complete. Here we show that incorporating a short juxtamembrane sequence into the EGFRt polypeptide enhances its expression on the surface of T cells and their susceptibility to antibody-dependent cellular cytotoxicity (ADCC). Incorporating this optimized variant (EGFRopt) into bicistronic and tricistronic CAR designs results in more rapid in vivo elimination of CAR T cells and robust termination of their effector activity compared to EGFRt. These studies establish EGFRopt as a superior safety switch for the development of next-generation cell-based therapeutics.

bioengineering↗

bioRxiv2020

De novo design of modular and tunable allosteric biosensors

Naturally occurring allosteric protein switches have been repurposed for developing novel biosensors and reporters for cellular and clinical applications 1, but the number of such switches is limited, and engineering them is often challenging as each is different. Here, we show that a very general class of allosteric protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which binding of a peptide key triggers biological outputs of interest 2. Using broadly applicable design principles, we allosterically couple binding of protein analytes of interest to the reconstitution of luciferase activity and a bioluminescent readout through the association of designed lock and key proteins. Because the sensor is based purely on thermodynamic coupling of analyte binding to switch activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We demonstrate the modularity of this platform by creating biosensors that, with little optimization, sensitively detect the anti-apoptosis protein Bcl-2, the hIgG1 Fc domain, the Her2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac Troponin I and an anti-Hepatitis B virus (HBV) antibody that achieve the sub-nanomolar sensitivity necessary to detect clinically relevant concentrations of these molecules. Given the current need for diagnostic tools for tracking COVID-19 3, we use the approach to design sensors of antibodies against SARS-CoV-2 protein epitopes and of the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein. The latter, which incorporates a de novo designed RBD binder, has a limit of detection of 15pM with an up to seventeen fold increase in luminescence upon addition of RBD. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions.

synthetic biology↗

bioRxiv2020

Improved bacterial recombineering by parallelized protein discovery

Exploiting bacteriophage-derived homologous recombination processes has enabled precise, multiplex editing of microbial genomes and the construction of billions of customized genetic variants in a single day. The techniques that enable this, Multiplex Automated Genome Engineering (MAGE) and directed evolution with random genomic mutations (DIvERGE), are however currently limited to a handful of microorganisms for which single-stranded DNA-annealing proteins (SSAPs) that promote efficient recombineering have been identified. Thus, to enable genome-scale engineering in new hosts, highly efficient SSAPs must first be found. Here we introduce a high-throughput method for SSAP discovery that we call Serial Enrichment for Efficient Recombineering (SEER). By performing SEER in E. coli to screen hundreds of putative SSAPs, we identify highly active variants PapRecT and CspRecT. CspRecT increases the efficiency of single-locus editing to as high as 50% and improves multiplex editing by 5 to 10-fold in E. coli, while PapRecT enables efficient recombineering in Pseudomonas aeruginosa, a concerning human pathogen. CspRecT and PapRecT are also active in other, clinically and biotechnologically relevant enterobacteria. We envision that the deployment of SEER in new species will pave the way toward pooled interrogation of genotype-to-phenotype relationships in previously intractable bacteria.

microbiology↗

bioRxiv2016

Millstone: Software for Multiplex Microbial Genome Analysis and Engineering

Inexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. We describe Millstone, a web-based platform which automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab.

synthetic biology↗

bioRxiv2016

Optimizing complex phenotypes through model-guided multiplex genome engineering

Optimization of complex phenotypes in engineered microbial strains has traditionally been accomplished by laboratory evolution. However, only a subset of the resulting mutations may affect the phenotype of interest and many others may have unintended effects. Multiplexed genome editing can complement evolutionary approaches by creating diverse combinations of targeted changes, but in both cases it remains challenging to identify which alleles influence the desired phenotype. We present a method for identifying a minimal set of genomic modifications that optimizes a complex phenotype by combining iterative cycles of multiplex genome engineering and predictive modeling. We applied our method to the 63-codon E. coli strain C321.{Delta}A, which has 676 mutations relative to its wild-type ancestor, and identified six single nucleotide mutations that together recover 59% of the fitness defect exhibited by the strain. The resulting optimized strain, C321.DA.opt, is an improved chassis for production of proteins containing non-standard amino acids. Our data reveal how multiple cycles of multiplex automated genome engineering (MAGE) and inexpensive sequencing can generate rich genotypic and phenotypic diversity that can be combined with linear regression techniques to quantify individual allelic effects. While laboratory evolution relies on enrichment as a proxy for allelic effect, our model-guided approach is less susceptible than enrichment to bias from population dynamics and recombination efficiency. We also show that the method can identify beneficial de novo mutations that arise adventitiously. Beyond improving the fitness of C321, {Delta}A, our work provides a proof-of-principle for high-throughput quantification of individual allelic effects which can be used with any method for generating targeted genotypic diversity.

synthetic biology↗