Trends in Biotechnology

Motivation: Retrobiosynthesis tools use different reaction rules, search strategies and biochemical priors, so each can recover transformations missed by others. Integrating their outputs could broaden pathway coverage, but ensembling can also worsen ranking. Results: SynBioCrow runs independent retrosynthesis engines, normalizes predictions into a provenance-preserving reaction graph, and separates route generation from biochemical evidence, sequence design and bounded learning. On the frozen 65-path Galaxy-SynBioCAD literature benchmark used for SynBioCrow 2.3, connectivity-level partial recovery was 19/65 for the ensemble, 13/65 for RetroBioCat2, 9/65 for RetroPath and 0/65 for DORAnet; the ensemble preserved two exact RetroPath routes but worsened their ranks. SynBioCrow 2.4 subsequently repaired structured-reaction parsing and target-connected Candidate generation and prospectively locked two new external targets, 1,3-propanediol and 1,4-butanediol, before pathway truth was examined. RetroBioCat2 produced 3 and 2 backend-internal SOLVED search outcomes, respectively, whereas DORAnet produced none; however, neither backend recovered any predeclared explicit literature intermediate by exact structure. The negative prospective result was frozen without post-reveal tuning. Production ranking in 2.4 is therefore NONE and the release remains Candidate-stage; validated complete-pathway recovery is not claimed. Availability: SynBioCrow 2.4.0 is archived at DOI 10.5281/zenodo.23173173 with source code and frozen supporting evidence.

Plasmid copy number (PCN) is a central determinant of recombinant gene expression levels and metabolic burden in bacterial cell factories. However, dynamic real-time control of PCN during microbial cultivation remains largely unexplored. In the ColE1/pUC19 replication system, PCN is governed by an antisense RNAI/RNAII circuit, but this native mechanism provides no external handle for process-level intervention. Here, we engineer and characterize a dual-layer control architecture that combines two orthogonal perturbations to direct plasmid replication in Escherichia coli populations i.e., temperature shifts, which modulate the secondary structure of RNAII and, consequently, its binding to RNAI and its inhibitory potency (ex vivo control), and arabinose-inducible overexpression of a supplementary RNAI cassette, integrated either on a secondary low-copy plasmid or directly on the high-copy target plasmid (in vivo control). Using a superfolder GFP validated fluorescent reporter and automated flow cytometry in continuous cultures, we track PCN dynamics at the population level in real time under chemostat conditions. Preliminary screening in microplates high-throughput cultivation device across three strains, two carbon sources, and three temperatures (30, 37, and 42C) reveals that the two control layers act synergistically. Neither temperature alone nor inducible RNAI alone achieves the dynamic range obtained by their combination. This synergistic effect is sustained during continuous cultivation at a fixed dilution rate of 0.1/h, with carbon source and temperature transitions producing predictable and reproducible shifts in population-level PCN. These results establish a scalable, dual-input framework for on-demand PCN tuning in continuous bioprocesses, with direct relevance to biopharmaceutical plasmid production and synthetic biology applications.

Directed evolution enables the engineering of proteins with novel or improved functions, yet existing approaches often require extensive manual intervention and are difficult to sustain over long evolutionary trajectories. Here we introduce PRIME (Protein-primed Replication for In vivo Mutagenesis and Evolution), a plasmid-based orthogonal DNA replication system for continuous directed evolution in Escherichia coli. PRIME harnesses protein-primed DNA replication to establish an autonomous replicon that operates independently of the host genome. Coupling this system to an error-prone DNA polymerase enables targeted diversification of constructs encoded on the orthogonal plasmid while preserving genomic integrity. Using only standard laboratory equipment, we demonstrate the evolution of a construct expressing msfGFP with an 11.8-fold increase in fluorescence. The platform is fully compatible with standard molecular biology workflows and requires no specialised instrumentation. We further demonstrate its portability across bacterial hosts by establishing PRIME in Pseudomonas putida. PRIME thus provides a broadly accessible framework for continuous in vivo evolution, with wide-ranging applications in protein engineering and synthetic biology.

Genome transplantation is a key technology for synthetic genomics, enabling entire genomes to be transferred into recipient cells. Despite its importance, genome transplantation remains confined to a small number of wall-less Mollicute species and is often characterized by low efficiencies, limiting the development and testing of synthetic genomes. Because genome transplantation relies on the same polyethylene glycol mediated DNA delivery process used for plasmid transformation, improving DNA uptake is an important step toward more efficient transplantation systems. Here, we systematically optimized polyethylene glycol-mediated transformation in Mesoplasma florum, a fast-growing, non-pathogenic Mollicute with a reduced genome that represents an attractive chassis for synthetic genomics. We evaluated 20 parameters spanning cell physiology, DNA preparation, membrane conditioning, and recovery conditions. DNA topology emerged as the strongest determinant of transformation efficiency, with highly compacted DNA preparations producing up to three orders of magnitude more transformants than conventional plasmid preparations. Growth phase and polyethylene glycol concentration also strongly influenced transformation outcomes. To identify potential recipients for future genome transplantation experiments, we further screened ten strains belonging to the Mesoplasma lineage. Transformation efficiencies varied widely among strains, and Mesoplasma entomophilum W17 emerged as a particularly promising candidate. Moreover, W17 supported replication of plasmids carrying the M. florum oriC, suggesting compatibility between the replication systems of the two species. Together, these results establish an improved transformation workflow for M. florum, identify DNA topology as a major determinant of DNA uptake, and reveal a new candidate recipient for future genome transplantation studies. These advances provide practical tools and biological insights for synthetic genome engineering in Mollicutes.

The valorisation of biological polymers requires microbial systems that can both access recalcitrant substrates and convert the resulting carbon into useful products. Although microbial genome and metagenome resources provide an expanding reservoir of candidate depolymerizing and modifying enzymes, most discovery workflows remain disconnected from enzyme optimisation and host adaptation. Here we present a coupled sequence-based enzyme discovery, enzyme evolution and synthetic yeast chassis adaptation strategy for microbial biopolymer valorisation. Focusing on laccases for the depolymerisation of lignin as a proof of concept, we combine sequence data mining for enzyme discovery, modular yeast surface display for functional screening, directed evolution for enzyme optimisation and synthetic yeast genome diversification for chassis improvement. In our study, surface display enabled functional benchmarking and recovery of improved laccase variants and synthetic-genome-enabled diversification provided a route to explore host configurations that influence display and enzyme performance. By integrating enzyme-level and chassis-level optimisation, this framework addresses a central bottleneck in converting microbial biodiversity by computational sequence repository mining into deployable biomanufacturing systems. Our results establish laccases as tractable entry points for oxidative biopolymer conversion and provide a generalizable platform for engineering yeast systems for sustainable carbon valorisation.

Massive library-based platforms enable rapid early hit discovery, yet subsequent hit resynthesis and validation remain major bottlenecks in drug discovery. This delay is amplified when optimizing hits, or elaborating structures towards more advanced modalities, such as chemical inducers of proximity (CIPs). Here, we report PROXINAUT, an end-to-end workflow integrating self-encoded library-based hit discovery with an automated parallel solid-phase synthesis platform to streamline hit discovery, validation, optimization, and degrader development. As a demonstration, screening a 176k-member benzimidazole library against BRD4 yielded six hit candidates, which were obtained via parallel automated synthesis and validated as submicromolar binders. The automation workflow empowered a rapid structure activity relationship exploration around the whole scaffold and resulted in a variant with six fold improved binding affinity. Next, we aimed to automatize the development of bifunctional degraders. Solid phase synthesis typically leaves a C-terminal amide as a synthetic artifact that can compromise druglike properties. We developed a strategy to repurpose this resin-attachment site, converting it into functional degrons featuring either FBXO31-targeting C-terminal amides or cereblon-binding cyclic imides. Operating without human intervention, our automated platform executes up to 16 synthetic steps across multiple parallel structures, enabling true de novo synthesis of full bifunctional scaffolds, where ligand, linker and E3 recruiter variations can all be explored within the same workflow. This resulted in cell-active BRD4 degraders with subnanomolar to nanomolar potency. Overall, we show how library selections can merge with multi-step parallel automation to convert hits directly into validated leads and advanced degrader modalities.

Synthetic endosymbiosis, the deliberate introduction of bacteria into eukaryotic host cells, provides a tractable model for how endosymbiotic relationships become established, and a route to cells with new metabolic capabilities that never evolved naturally in that lineage. Current methods for introducing bacteria into mammalian cells rely on microinjection, engineered invasion, listeriolysin-mediated phagosomal escape, or naturally permissive hosts. These methods are invasive, low-throughput, or costly, and most require the prospective endosymbiont to be genetically tractable, which excludes endosymbiotic bacteria which are of great interest as potential organelle precursors. Here we describe a protocol based on polyethylene glycol (PEG), long used to fuse mammalian cells, that delivers Escherichia coli into HeLa cells without genetic modification of either partner or the use of specialised equipment. We optimised the governing parameters in two stages: first, bacterial density, gentamicin concentration, and PEG molecular weight and concentration were optimised; then, medium composition and the timing of fusion and recovery. Across four parameters screened, 10% PEG-3350 applied for 4 min to HeLa cells 12 h after seeding, followed by 4 h in gentamicin-containing medium, gave the most consistent delivery. Under these conditions, confocal microscopy and z-stack reconstruction detected mCherry-tagged E. coli inside HeLa cells. Applying the same protocol to Candidatus Kinetoplastibacterium crithidii, a naturally occurring {beta}-proteobacterial endosymbiont of the trypanosomatid Angomonas deanei, we observed the endosymbiont inside the HeLa cells. This protocol offers an accessible entry point for constructing artificial endosymbioses.

Autonomous experimentation, where an automated system designs, performs, analyzes, and iteratively improves experiments with minimal human intervention represents a transformative scientific research paradigm. However, it remains hampered by the disconnect between computational design and experimental execution. Here we present iCloudBiofoundry, a cloud-accessible, scalable, and self-evolving platform that bridges this divide. A scientific multi-agent system, iBioGenie, plans research workflows by converting natural language research objectives into testable hypotheses and experimentally grounded protocols using literature, databases, and computational tools. A physical AI layer, BiofoundryAI, translates them into executable workflows that run autonomously on distributed robotic biofoundries, and collects the data for iterative design. We demonstrate the end-to-end capabilities of iCloudBiofoundry across three representative case studies spanning enzyme retrieval, protein engineering, and metabolic engineering. By integrating agentic AI with physical AI, iCloudBiofoundry provides a cloud accessible platform that unifies computational design and robotic execution, enabling autonomous biological research.

Bacterial conjugation and CRISPR base editing offer complementary routes for programmable DNA transfer and heritable genomic writing, but their combined potential for information encoding in living cells remains unexplored. Here, we introduce CONCORD, a bacterial encoding platform that couples multiplexed bacterial conjugation to genomic base editing for synthesis-free in vivo DNA data writing. A recipient Writer strain expresses the base-editing machinery and is equipped with a writing template, whereas reusable donor Guide strains deliver the encoding sgRNA signals by conjugation. Using this setup, we encode binary information into genomic DNA in a high-throughput manner. Moreover, we systematically evaluated multiple orthogonal base editors for an expanded encoding repertoire and improved data recovery through redundancy encoding. We deploy the system to encode 45,689 bits into DNA including two culturally and historically significant artifacts: a greeting from NASA's Voyager Golden Record and a photograph of Navajo petroglyphs and recovered these datasets with 100% and 99.5% accuracy, respectively, without computational error correction. Connecting and engineering the unique mating and immune system of microbial cells we have established a framework for programmable information writing in bacterial populations, with applications for biological event recording and sustainable DNA data storage.

Engineering proteins at the scale of modern high-throughput screening technologies remains challenging because most experimental libraries sample only limited regions of sequence space while maintaining relatively low levels of functional diversity. Although recombination-based strategies can introduce substantially larger sequence changes than conventional mutagenesis approaches, it is unclear whether highly recombined enzymes can retain catalytic competence when library sizes approach millions to billions of variants. To investigate this question, we constructed a recombination library by combining ten sequence blocks from ten bacterial PETases, generating a theoretical diversity of 10^8 chimeric enzymes. Screening of yeast-displayed libraries using a fluorophosphonate probe for catalytic-serine reactivity identified substantial populations of catalytically competent variants despite extensive sequence recombination and dozens of amino acid substitutions per chimera. Approximately 2% of sampled variants possessed active-site serine reactivity, corresponding to an estimated 10 catalytically competent enzymes within the full theoretical library. Deep sequencing showed that functional populations remained broadly distributed across sequence space following selection and contained multiple enriched recombination patterns spanning the PETase structure. Secondary lysate screening and enzyme-normalized activity measurements further identified multiple purified PETase chimeras with soluble esterase activity comparable to or greater than the wild type Ideonella sakaiensis PETase on a chromogenic surrogate substrate. Together, these results demonstrate that large-scale recombination can generate millions of diverse and catalytically competent enzymes while remaining compatible with modern high-throughput screening workflows. More broadly, this work establishes recombination-based diversity generation as a scalable strategy for protein engineering and large-scale sequence-function data generation.

Electromicrobial production (EMP) technologies aim to combine renewable electricity, CO2, and engineered microbes to make energy-dense molecules at efficiencies exceeding photosynthesis. CO2 can be electrochemically reduced to formate, which is far easier to handle at the bench than H2 or an electrode, but formate carries only two electrons per carbon against the six in a biofuel. The remaining electrons must come from oxidizing additional formate, from H2 oxidation, or from extracellular electron uptake (EEU), and no rigorous comparison of these options coupled to the choice of carbon assimilation pathway currently exists. We calculate upper-limit efficiencies for butanol production by six carbon assimilation pathways, each paired with all three electron delivery mechanisms, using electrochemical parameters drawn from a survey of the recent literature. Electrical to butanol energy conversion efficiencies range from 35.5 to 51.7%, corresponding to solar-to-fuel efficiencies of 11.7 to 17%, so even the least efficient route exceeds the 8% theoretical ceiling of algal photosynthesis. The serine variant of the reductive glycine pathway reaches an electrical energy conversion efficiency of when using H2 oxidation, within 1.9 points of the most efficient pathway, and is the only high-efficiency option that tolerates O2. This makes an EMP system that combines electron delivery by formate coupled with the serine variant of reductive glycine pathway highly attractive, as it presents few barriers to rapid, iterative engineering in the lab, and a high theoretical ceiling. Drawing both carbon and electrons from formate costs 6.2 points against H2 at a state-of-the-art whole-cell voltage (2.2 V). However, this small penalty is amplified three-fold by any rise in the CO2-to-formate cell voltage, and reaches 13.5 points at the highest whole-cell voltages reported for scaled-up CO2-to-formate electrolyzers, where formate-only operation falls to 11.2 electrical-to-fuel and 3.7% solar-to-fuel efficiency, below the ceiling of photosynthesis, against 24.7 and 8.1% for H2 (only just above algal photosynthesis). Our choice between a formate-only system and one coupled to H2 oxidation or EEU therefore depends on our belief about the trajectory of CO2 reduction technology. If whole-cell voltages continue to fall at the rate of the past decade, formate alone is the right target, and the simplicity of its workflow is bought at low cost. However, if that improvement plateaus, the electron delivery mechanism must be swappable, and a system should be designed from the outset so that it can be. At the US Department of Energy SunShot target of 2 cents per kilowatt hour, the electricity to make a US gallon of butanol costs $1.40 for a formate-only system at the state of the art, rising to $5.45 at the highest scaled-up electrolyzer voltage reported, against $1.23 and $2.47 for formate and H2 system.

Engineering G protein-coupled receptors (GPCRs) for biosensing applications remains challenging due to structural and functional constraints when such proteins are expressed in a heterologous host. OrthoRep offers the continuous accumulation and selection of signal-enhancing mutations in yeast, yet it has not been applied to GPCR evolution. We apply OrthoRep-driven mutagenesis to evolve opioid GPCRs and improve yeast-based biosensors: first, we express the human -opioid receptor (OPRM1) on the OrthoRep p1 plasmid and couple ligand activation to growth. Serial cell passaging of the biosensor generated functionally diverse mutants. However, mutations that decouple receptor activation from selection arose over longer passaging campaigns, halting evolution. We resolve this issue using a site-specific recombinase that re-introduces evolved variants onto the p1 landing pad of an unmutated biosensor, allowing continued selection. This led to an ~18-fold improvement in sensitivity of a mutant OPRM1 over wt-OPRM1. Additional polymerases were added to the platform, broadening the mutational profiles available. Assembling these components forms the platform we call HERO (Heterologous Engineering of Receptors using OrthoRep). Lastly, we deploy HERO using automation to improve the human {delta}-opioid receptor's weak response to an agonist by ~40-fold. Sensitivity also improved for a structurally dissimilar ligand assayed on the same evolved variants.

Functional protein micro/nanofibers integrate high specific surface areas with bioactive architectures but remain hampered low production throughput and severe processing instability. Focused rotary jet spinning (FRJS) shows promising to break these throughput constraints while enabling direct, conformal deposition onto complex, irregular substrates. However, navigating FRJS's narrow processing windows in proteins remains failure-prone without closed-loop experimental guidance. Here, we report FiberPro 1.0, a large language model driven multi agent framework that unites high-throughput spinning with real-time experimental feedback for autonomous design, execution, and optimization. Across three protein systems, FiberPro 1.0 converged on spinnable formulations within an average of two iterations. To demonstrate high-throughput conformal deposition in a translational setting, FiberPro designed a zein-based active packaging system applied directly onto diverse food matrices. The resulting conformal coating combined potent antibacterial activity with real-time freshness monitoring, markedly suppressing Escherichia coli and extending shelf life. This work connects autonomous AI reasoning with high-throughput processing, establishing a verifiable route for scalable manufacturing and conformal coating of functional protein micro/nanofibers.

Influenza A virus (IAV) defective interfering particles (DIPs) are regarded as promising broad-spectrum antivirals due to their high efficacy demonstrated in animal trials. Previously, an OP7 chimera DIP was generated that showed markedly enhanced antiviral efficacy compared to conventional IAV DIPs. In addition, a high-yield cell culture-based production process for OP7 chimera DIPs was established in perfusion mode. However, due to the technical complexity of this technology, we aimed to combine the advantages of perfusion in terms of yield with that of a simple and less complex batch process. In the present work, we established a fed-batch production process for OP7 chimera DIPs that allows a more straightforward implementation into existing production facilities. Using a feeding regime that was able to overcome the cell density effect, we achieved productive virus infection in stirred tank reactors until a cell density of 10E+6 cells/mL. Furthermore, we obtained a high virus titer of 3.8 log10(HAU/100 uL), corresponding to a 3.4-fold increase compared to a reference batch production. Moreover, the produced material demonstrated a significantly increased interfering bioactivity shown by an in vitro potency assay. Interestingly, this efficacy was similarly high as compared to OP7 chimera DIP material previously produced in perfusion mode, despite twofold lower virus titers. Finally, we demonstrate robustness of OP7 chimera DIP seed virus trains, which is significant step towards later pharmaceutical production. Further, corresponding GMP MDCK-PB2(sus) cell and OP7 chimera virus banks are now available for later biomanufacturing further use. In conclusion, the established fed-batch process offers a valid n additional option for pharmaceutical grade OP7 chimera DIP GMP manufacturing production under GMP conditions required for subsequent clinical testing and for later large-scale manufacturing.

Many therapeutically relevant signaling pathways are sensed inside the cell, yet a modular synthetic biology platform for responding to intracellular signaling at the post-translational level is lacking. Signaling pathways control the nuclear localization and activity of native transcription factors via phosphorylation of nuclear localization/export or cytoplasmic anchor sequences. Here, we apply this concept to develop a platform of nucleocytoplasmic localization tags (NCtags) that control the nuclear translocation of a synthetic transcription factor (synTF) for transgene induction in engineered cells. We identify human-based synTF components that are basally cytoplasmic and induce transgenes under the control of NCtags with minimal background. We demonstrate the modular nature of this platform through transcriptional reporter induction in response to a calcium-inducible NFAT-derived NCtag, and development of novel NCtags responsive to hyperosmolarity, cAMP, or logical combinations of cAMP and calcium. Multiple factors in the tumor microenvironment elevate cAMP in T cells, leading to reduced function. We demonstrate that NCtag-synTF fusions expressed in T cells can respond to endogenous sources of cAMP or calcium in breast cancer spheroids to induce transgene expression. Our use of human components and an all-in-one lentiviral vector encoding the NCtag-synTF-transgene system establishes this as a novel platform for sense-and-response inside therapeutic cells.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a leading global health threat, especially due to multidrug-resistant strains. The first-line drug isoniazid (INH) and second-line drugs ethionamide (ETH) and prothionamide (PTH), are prodrugs that target the essential enoyl-ACP reductase InhA, a key enzyme involved in mycolic acid biosynthesis. Resistance to these drugs primarily arises from genetic mutations that inactivate the enzymatic function of their respective bioactivating enzymes. While the recent development of chemical boosters has shown promising results in restoring drug susceptibility in these mutants, genetic tools to dynamically modulate these pathways and fine-tune resistance could be extremely valuable to develop the next-generation of anti-InhA drugs. In this context, we leverage CRISPR interference (CRISPRi) to develop inducible and reversible genetic systems to fine-tune antibiotic susceptibility in Mycobacterium smegmatis (Msmeg) and Mtb. By using our CRISPRi-based approach we first generated an inducible inhA hypomorph, an essential target required for mycolic acid production and bacterial growth, therefore confirming that our method is fully functional. Then, we developed genetic tools to selectively target katG, ethA, and the transcriptional repressor ethR, in order to generate conditional hypomorphs with altered antibiotic susceptibility profiles. Antibiotic susceptibility assays confirmed that the conditional hypomorphs selectively displayed high-level resistance or hypervulnerability to INH or ETH upon CRISPRi induction. Altogether, this work establishes CRISPRi as a powerful genetic platform for selectively fine-tuning mycobacterial drug susceptibility, with potential applications in developing next-generation anti-TB therapies.

Adeno-associated virus (AAV) vectors are widely used for gene delivery to the central nervous system, but natural capsid tropism is broad and cell-type restriction is typically imposed transcriptionally using promoters and enhancers that consume packaging capacity and often drive weak expression. Here, we engineer neuronal targeting directly into the AAV-DJ capsid by ablating its endogenous heparan sulfate proteoglycan (HSPG) affinity and genetically displaying a nanobody against the Group 1 metabotropic glutamate receptor mGluR5 within the VP1 subunit at a permissive capsid loop (T456), generating AAV-m5. Western blot confirmed incorporation of the nanobody-VP1 fusion into assembled capsids. In primary hippocampal neuron cultures, ablating HSPG binding abolished infectivity and nanobody display rescued transduction while restricting GFP expression almost exclusively to mGluR5-positive neurons. Heparin competition assays showed that, unlike wild-type AAV-DJ, AAV-m5 transduction was unaffected by exogenous heparin, confirming that entry occurs independently of HSPG binding. Packaged with a strong constitutive promoter (CAG), AAV-m5 achieved neuron-restricted expression comparable to or exceeding that of wild-type AAV-DJ driven by a neuron-specific promoter (hSyn) and produced negligible expression under an astrocyte-specific promoter (GFAP) despite promoter activity in glia, demonstrating that capsid-level targeting can substitute, or complement, transcriptional restriction. Following stereotactic injection into the mouse hippocampus, AAV-m5 achieved an eight-fold higher proportion of transduced neurons than wild-type AAV-DJ at equivalent titers. Delivery to Grm5-null hippocampus reduced both the intensity and the spatial extent of transduction, confirming that the broad hippocampal transduction achieved by AAV-m5 is mGluR5-dependent. Together, these results establish nanobody-functionalized AAV-DJ as a modular, single-component platform for precision CNS gene delivery that circumvents the packaging and expression trade-offs of promoter-based cell-type restriction, with potential for retargeting to additional CNS cell types and disease-relevant receptors.

Reliable constitutive promoters for non-model bacteria are lacking, resulting in a bottleneck for genetic tool development. Existing computational promoter predictors are trained on model Gammaproteobacteria and degrade on phylogenetically distant or compositionally atypical genomes. Here we present ProFinder, a computational method that integrates three biologically informed criteria for promoter prediction: a conserved 98-gene constitutive marker panel, an empirically derived intergenic search window, and a 72-motif {sigma}70 motif catalogue built from diverse lineages. From an input bacterial assembly, ProFinder returns a ranked shortlist of putative constitutive promoters. It matches the precision of full-genome classifiers and is more robust to GC extremes. Applied to 56,742 bacterial genomes spanning 149 phyla, ProFinder returned candidate promoters for 99.76%, delivering a pan-bacterial catalogue of pre-computed constitutive promoter parts to accelerate chassis development across the bacterial tree. ProFinder can be accessed at: https://plabase.cs.uni-tuebingen.de/profinder/.

Adeno-associated virus (AAV) mediated gene therapies continue to show promise for the treatment of genetic diseases. However, delivery and safety still represent significant prohibitive barriers restricting translation of these delivery modalities to humans. We describe a novel AAV9 variant, AAV9fyhr or FYHR, identified from screening a controlled randomization point mutation AAV9 library in mice and nonhuman primates followed by directed evolution of in vivo CNS-derived libraries screened in human iPSC differentiated cortical neurons. Capsid variants of interest were identified by coupling long read sequencing and computational structure modeling. Structure-function analysis of our lead candidate reveal that two targeted amino acid changes are sufficient to result in beneficial pleiotropic effects across viral stability, cell surface attachment, and gene delivery. We developed a novel multiplexed barcoding reporter system, enabling a time and cost-effective option to gather spatially resolved single cell capsid validation data in mice and nonhuman primates. When administered intrathecally, AAV9fyhr exhibits 2-to-6-fold higher gene delivery across several tissues in the CNS while minimally altering the tropism to peripheral tissues in comparison to AAV9. These findings demonstrate the potential of whole capsid engineering for the rational development of translational next generation AAV capsids.

Macromolecular release from synthetic cells often relies on membrane pores or channels. We explored whether internally generated osmotic stress could increase membrane permeability and promote release. Using double-emulsion microfluidics, we encapsulated an Escherichia coli cell-free expression system in Pluronic L121 polymersomes to co-express the fluorescent protein mScarlet3 and the dextranase PsDex1711 in the presence of dextran. PsDex1711-mediated dextran hydrolysis produced a greater increase in bulk osmolality than reactions without PsDex1711 DNA. Tracking hundreds of individual polymersomes showed that PsDex1711-containing populations expanded, whereas control populations contracted. The distribution of normalized fluorescence revealed a subset with lower residual fluorescence than the main population. In selected expanded polymersomes, integrated internal mScarlet3 fluorescence declined to 18-22% of peak levels, without visible membrane disruption, consistent with protein release. These findings support a proof of concept for using internal gene expression to promote macromolecular release through osmotic actuation without introducing dedicated membrane pores.