ACS Synthetic Biology

SynNotch-CAR circuits improve T cell specificity by coupling antigen recognition to inducible CAR expression. However, basal CAR expression without receptor activation, termed here as leakiness, can reduce the separation between killing of intended target cells and sparing of antigen-positive off-target cells, limiting target-cell discrimination. Here, we systematically quantified basal CAR expression for several synNotch-CAR designs and developed a coupled ordinary differential equation model to show that discrimination depends on basal output, CAR potency, and effector-to-target ratio. We introduced C-terminal tags such as fluorescent proteins, degron domains, endocytosis signals, and endoplasmic reticulum retention motifs as a strategy to reduce CAR leakiness. We found that fluorescent proteins and degron-containing tags reduced basal CAR surface expression while preserving antigen-induced CAR expression, improving discrimination of antigen-density sensing and combinatorial circuits in vitro. In xenograft models, fluorescent protein-tagged CARs improved discrimination by reducing activity against off-target cells while retaining activity against high-antigen tumors. Degron-containing constructs reduced basal CAR expression in vitro but showed suboptimal performance in vivo, revealing a trade-off between basal CAR suppression and induced CAR persistence. Together, these findings demonstrate that basal output expression is a key parameter for inducible genetic circuit designs and establish layered transcriptional and post-translational regulation as a strategy to improve the fidelity of inducible T cell circuits.

Maintaining a prescribed composition in engineered microbial consortia is difficult because small fitness differences can drive competitive exclusion. We study a two-strain consortium in continuous culture and develop a feedback architecture that regulates composition by selectively slowing the fast strain as a function of the population ratio. At the population level, we derive an idealized ratio-feedback law with a tunable positive coexistence equilibrium. We then propose a biomolecular realization using orthogonal quorum sensing, an sRNA-based ratiometric controller, and a ppGpp-mediated growth actuator. Exploiting the separation between slow population growth and faster intracellular controller dynamics, we use singular perturbation theory to show that, for sufficiently fast controller dynamics, the full implementation model inherits the coexistence equilibrium and its local stability properties from the reduced model. Numerical simulations validate the reduction and show how weaker timescale separation or loss of the assumed molecular regime degrades performance.

Hybridoma screening in semi-solid medium typically employs antigens labeled with visible fluorophores (e.g., FITC, AF488) to enable single-step identification of antibody-secreting clones. However, conventional chemical conjugation via NHS-esters or isothiocyanate groups frequently modifies lysine residues located within epitopes, potentially abrogating antibody recognition of these critical regions. Here, we describe a SpyTag SpyCatcher-based site-specific labeling strategy that circumvents epitope damage during semi-solid medium screening. A 16-amino-acid SpyTag was genetically fused to the C-terminus of the target antigen, enabling covalent conjugation to an sfGFP SpyCatcher fluorescent probe. In semi-solid medium supplemented with SpyTag-antigen and sfGFPSpyCatcher, positive hybridoma clones were readily identified by distinct fluorescent halos, whereas negative clones showed no detectable signal. Notably, the site-specific method yielded a significantly higher frequency of fluorescence-positive clones compared to the conventional AF488-labeled antigen method, suggesting that epitope preservation enhances screening recovery. Furthermore, this approach did not impair hybridoma growth or final clone positivity, offering a simple, rapid, and epitope-compatible method for monoclonal antibody screening.

Cell motility drives spatial pattern formation across diverse biological systems. Here, we engineer Escherichia coli motility in semi-solid agar to control Voronoi patterns in two and three dimensions, partitioning space into regions closest to their respective inoculation seeds. Consistent with our reaction-diffusion model, we observed that collisions between expansion fronts generate either biomass depletion (''gaps'') or accumulation (''anti-gaps''), governed by the relative diffusion rates of bacteria and nutrients. By engineering strains with distinct expansion rates and tuneable motility, and by integrating these experimental data into a dynamic Voronoi model, we achieved precise control over pattern geometry. This enabled the generation of gaps with varying widths, curved boundaries, asymmetric structures, seedless regions, and complex composite patterns. Together, these findings establish bacterial Voronoi patterns as a programmable platform for engineering multicellular spatial organization, with potential applications in synthetic biology and materials science.

The dynamics of gene regulatory networks are governed by intrinsic noise, stemming from the random nature of biochemical reactions, and by extrinsic noise, arising from fluctuations in cellular components and environmental conditions. Together, these sources can compromise the reliability of predictive computational models if not properly accounted for, and capturing both effects within a single framework remains a non-trivial task in computational biology. In this work, we propose an uncertainty quantification framework that addresses these two contributions jointly: intrinsic stochasticity is described through a partial integro-differential equation (PIDE) for the protein probability density function, whereas extrinsic noise is represented as parametric uncertainty in the kinetic parameters. The propagation of the uncertainty is carried out via an intrusive polynomial chaos expansion (PCE), in which the PCE coefficients are obtained from a stochastic Galerkin projection of the PIDE, yielding a coupled deterministic system that is solved with standard numerical methods. We illustrate the approach on a positive autoregulatory gene network with one and two uncertain kinetic parameters. The proposed approach accurately reproduces the mean, variance, and full protein probability density function, including the bimodal distributions, at a substantially lower computational cost.

The binding affinities of a chimeric analog of a riboflavin derivative linked to biotin, (6- (7,8-dimethyl-2,4-dioxo-3,4-dihydrobenzo[g]pteridin-10(2H)-yl)hexyl 5-((3aS,4S,6aR)-2- oxohexahydro-1H-thieno[3,4-d]imidazol-4-yl)pentanoate), referred to as C6-Rf-biotin-tag, to the riboflavin binding retain or streptavidin are in the M range, 1.29 {+/-} 0.277 and 3.00 {+/-} 0.459, respectively. These values suggest that C6-Rf-biotin-tag has potential applications in diagnostic assay and labelling target flavin binding proteins. The C6-Rf-biotin-tag which was characterized with respect to physical and biochemical properties retains UV/Vis spectroscopic and fluorescence behavior similar to riboflavin.

Methods for installing synthetic functions on living cell surfaces provide powerful approaches for imaging, sensing, and manipulating cell behavior, but many require genetic modification of the target cell or chemical modification of the plasma membrane. Here, we repurpose the glycosylphosphatidylinositol-anchored protein (GPI-AP)-binding toxin aerolysin as a modular chassis for non-genetic cell-surface functionalization. We show that a non-cytotoxic, monomeric aerolysin mutant retains high-affinity and GPI-AP-dependent cell binding when genetically fused to diverse protein cargos. Fluorescent protein-aerolysin fusions robustly label multiple cell types and remain predominantly associated with the cell surface for at least 24 h, in contrast to wheat germ agglutinin, which is extensively internalized. Aerolysin can also be equipped with SpyTag/SpyCatcher to enable modular assembly with independently expressed protein cargos. Importantly, aerolysin supports functional rather than solely optical modification of the cell surface: fusion to the proximity-labeling enzyme APEX2 enables extracellular protein biotinylation, while fusion to HUH endonuclease tags enables covalent attachment of synthetic DNA to living cells. Using this latter architecture, we developed a DNA hairpin sensor that converts cell-surface nuclease activity into a fluorescent signal and distinguishes cells with different levels of extracellular nuclease activity. Together, these results establish non-cytotoxic aerolysin as a genetically encoded, soluble adapter for installing proteins, enzymes, and programmable nucleic acids onto living cells without modification of the target-cell genome.

Phage tail-like elements (PTEs) -- tailocins, bacterial type VI secretion systems (T6SS), and extracellular contractile injection systems (eCIS) -- are contractile nanomachines that bacteria use to kill their neighbors and compete within their micro-ecosystems. PTEs help shape microbial community composition. Most PTE detection tools only detect a single PTE class. Moreover, most tailocin detection methods are largely restricted to Pseudomonas, leaving a key part of tailocin diversity uncharacterized. In this work, we present PhageTAILor (https://github.com/hjcho-bio/PhageTAILor), an integrative and fully automated pipeline that detects and classifies prophages and 3 PTE classes from bacterial genomes. PhageTAILor combines a 6-detector homology-based candidate search (geNomad, tail-gene, PHROGs-tail, SecReT6, eCIStem, and a divergence-tolerant tail-HMM detector) with a LightGBM classifier comprising 1 multiclass and 3 binary heads, trained on 6,501 bacterial genomes carrying 13,082 prophages and PTEs. A phylogeny-free feature matrix used in our model keeps predictions reproducible between model construction and user inference. PhageTAILor performs strongly at the genome level and generalizes beyond its Pseudomonas-rich training set. On a 76-strain cross-clade benchmark, PhageTAILor detected tailocins at F1 = 0.955. Furthermore, it identified 12 of 13 experimentally validated tailocins spanning five genera versus 2 of 13 for a Pseudomonas-restricted tool TattleTail. PhageTAILor also demonstrated sensitivity equivalent to viral detection tool geNomad while avoiding its higher false-positive rate. Applied to 7,925 plant- and soil-associated bacterial isolates, PhageTAILor showed that prophages in the phyllosphere and tailocins in plant-associated bacteria, whereas eCIS are enriched in soil. PhageTAILor is distributed as an open-source, modular pipeline with a command-line interface.

Motivation: Interactive tools that let non-programmers explore an analyzed single-cell dataset, its embeddings, gene expression, cell metadata, and marker genes, have become standard laboratory infrastructure. Every actively maintained tool in this space (ShinyCell, ScRDAVis, sCIRCLE, scViewer) is built on R Shiny and requires a Seurat object as input. Laboratories whose primary analysis pipeline is Python/scanpy, the dominant framework for single-cell RNA-seq, spatial, and multi-omic analysis, therefore have no lightweight, language-native option that pairs a shareable web-based viewer with a scriptable Python API: sharing a scanpy result means either exporting to Seurat first or handing over a notebook that only a programmer can run. Results: We present scPyviewer, a web-based viewer that ingests AnnData objects directly and reproduces the core interaction patterns of the incumbent R Shiny tools without leaving the Python stack. In a feature-parity audit against three actively maintained R Shiny incumbents, scPyviewer matches or exceeds every baseline capability (7/7); among these, it uniquely offers native AnnData ingestion with no Seurat conversion, and cross-dataset comparison over shared genes and matched cell-type composition. Benchmarked head-to-head against the R/Seurat rendering substrate the incumbents are built on, identical operations, identical data, across three datasets spanning 22,315 to roughly 313,000 cells, scPyviewer renders every core view faster at every scale tested (up to 3.6x on a single view) and at a fraction of the memory (5.2x lower on the smallest dataset). At the largest scale tested, the gap becomes categorical rather than incremental: scPyviewer completes every view on a 313,000-cell dataset while the Seurat substrate exhausts an 8 GB memory budget and fails outright. Beyond the interactive app, scPyviewer installs via pip or conda and exposes a public Python API that returns Matplotlib figures and pandas tables for scripted, publication-ready output. Availability and implementation: scPyviewer is implemented in Python 3.11 (scanpy 1.11.5, anndata 0.12.19, streamlit 1.59.2, plotly 6.9.0) and distributed with a one-command reproduction interface that installs pinned dependencies, regenerates the benchmark and all figures, and launches the interactive app. Source code is available at https://github.com/xuan13hao/scPyviewer.git.

Cyclic oligosaccharides possess industrial advantages, including molecular encapsulation capability and high physicochemical stability, owing to the absence of a reducing end. Recently, a novel cyclic tetrasaccharide, cycloisomaltotetraose (CI4), consisting of four -1,6-linked glucose units, and the enzymes responsible for its synthesis, cycloisomaltotetraose glucanotransferases (CI4Tases), were discovered. Unlike known cycloisomaltooligosaccharide glucanotransferases (CITases) that yield a wide distribution of cyclic products with a degree of polymerization (DP) of 7 or higher, CI4Tases strictly produce CI4. To elucidate the molecular mechanism underlying this strict DP4 specificity, we determined the crystal structures of CI4Tase from Agreia sp. D1110, in its ligand-free form, as well as in complex with the linear hydrolysis product isomaltotetraose (IG4) and with CI4. Structural comparisons revealed that a loop (M247 to R251) blocks the region corresponding to the -5 subsite of typical CITases, narrowing the substrate-binding pocket. This "molecular ruler" mechanism ensures that only a glycan chain of exactly four glucose units is accommodated for cyclization. Among mutants of the residue positioned at the center of bound CI4, the formation of by-products other than CI4 was significantly suppressed in F245L, F245A, and F245W. While the cyclization activity of all F245 mutants decreased, the CI4 hydrolysis activity of these three mutants was also significantly reduced, resulting in an increased specificity for cyclic sugar production. These findings elucidate the strict size-control mechanism of CI4Tase and provide a structural foundation for engineering cycloisomaltooligosaccharide-producing enzymes with optimized transglycosylation efficiency and specificity for industrial applications.

MicroRNAs (miRNAs) are key post-transcriptional regulators of development, stress response, and secondary cell wall formation in woody plants, yet annotations for Eucalyptus grandis, the world's most widely planted hardwood, remain fragmented across studies using incompatible discovery pipelines and filtering criteria. Here we present the Eucalyptus MicroRNA Archive (EMA), a curated, locus-resolved database integrating three independent small RNA sequencing datasets spanning vegetative tissue, somatic embryogenesis, and mechanically induced tension wood formation. Applying annotation criteria aligned with current plant miRNA standards, EMA catalogs 99 curated miRNAs (31 previously described, 68 novel) organized into 34 family-level groupings under a three-tier confidence system, known-reference-supported, multi-study replicated, or single-study, that preserves study-of-origin and sample-level evidence for every entry. Cross-study comparison showed that only 9 of 99 entries (9.1%) were independently supported by all three datasets, supporting an evidence-tiered rather than binary annotation scheme. Target prediction against the E. grandis transcriptome yielded 1,773 miRNA-target interactions spanning 764 loci, integrated into a combined miRNA-target and protein-protein interaction network. This network resolved into functionally coherent, mutually isolated clusters, including an miR482-associated NBS-LRR/TIR disease-resistance hub with a substantial translational-repression component, alongside modules enriched for ribosome biogenesis and translation, DNA replication, and nitrogen and carbohydrate metabolism. EMA is publicly accessible through an interactive web dashboard, with all curated data, source code, and analysis scripts openly available, providing a reproducible, extensible framework for E. grandis miRNA research and a template for similarly structured resources in other non-model woody species.

Botulinum neurotoxins (BoNTs) comprise a highly diverse group of seven serotypes (from A-G) and over 40 subtypes worldwide. Previous primer- and probe-based nucleic acid amplification tests (NAATs) for detection of BoNT encoding genes are challenged by high levels of nucleotide polymorphism both across and within subtypes. In this study, multiple BoNT gene sequences were aligned to identify highly conserved regions for the design of new primers that enable the detection of all seven serotypes under the same conditions. Specific primer sets were designed and validated using in silico, conventional and real-time PCR with constructed plasmids carrying the target fragments and spiked food matrices. The established procedure achieved highly specific and sensitive detection of BoNT serotypes A-G with sensitivity of 10 copies/reaction and a total turnaround time of approximately 1.5 hours. The procedure also eliminated the carryover PCR product by using uracil-N-glycosylase in combination with dUTP in the assay reaction mix. This study provides an alternative NAAT with higher coverage and compliments the traditional mouse bioassays in enhancing global botulism surveillance capabilities.

Biomolecular condensates (BMCs) organize cellular biochemistry by concentrating selected molecules into dynamic membrane-free compartments. Yet the molecular parameters that determine not only whether condensates form, but also how they behave and what they do, remain poorly defined. Here we show that scaffold binding affinity (Kd) is a quantitative determinant of condensate phase behavior, internal dynamics and biochemical output. Using a modular SUMO-SIM system in which scaffold valency was held constant while binding affinity was systematically varied, we found that affinity governs the phase boundary, resistance to chemical perturbation, and molecular mobility of condensates in vitro and in human cells. In multicomponent mixtures, the highest-affinity scaffold dominated dense-phase composition and dynamics, revealing a hierarchical rule for condensate organization. Finally, affinity-dependent changes in condensate dynamics translated into tunable enzyme activity, establishing binding energetics as an engineerable parameter for programming condensate biochemistry.

We report the generation and characterization of a human induced pluripotent stem cell (iPSC) line derived from dermal fibroblasts of a patient with Skogholt disease, a rare maternally inherited neurodegenerative syndrome associated with choroid plexus dysfunction and impaired cerebrospinal fluid (CSF) homeostasis. Patient fibroblasts were reprogrammed using the non-integrating Repro-OSKGM kit. The resulting iPSC line exhibited typical pluripotent morphology, expressed canonical pluripotency markers, maintained a normal karyotype, retained the disease-associated genetic variant, was mycoplasma-free, and demonstrated trilineage differentiation potential. We also made choroid plexus (ChP) like organoids from the generated iPSCs. This patient-specific iPSC line provides a valuable resource for generating choroid plexus organoids and neurons to investigate disease mechanisms and develop therapeutic strategies.

Autosomal dominant retinitis pigmentosa (adRP) caused by RHO mutations is a leading form of inherited retinal degeneration. Extensive allelic heterogeneity of RHO pathogenic variants limits the translational applicability of mutation-specific gene therapies. To address this, we developed SNARE (SNP-guided Silencing of Aberrant RHO Expression), a mutation-independent, allele-specific antisense oligonucleotide (ASO) strategy. SNARE selectively suppresses mutant RHO transcripts by targeting the common, benign c.-26A/G single-nucleotide polymorphism (SNP) as an allelic discriminator. Candidate gapmer ASOs were screened in engineered reporter lines and validated in patient-derived retinal organoids, identifying RHOligo-A as the lead c.-26A-targeting candidate. In vitro, RHOligo-A achieved robust, preferential knockdown of the target allele, improving RHO localization in retinal organoids, and demonstrated a favorable safety profile with minimal transcriptomic off-target effects and no detectable immunostimulatory activity. Subsequent validation in a novel, humanized RHOP347L/WT mouse model, achieved sustained c.-26A-linked allele-selective suppression, retinal structure preservation, and significantly restored visual function, upon a single intravitreal administration. These findings establish RHOligo-A and SNARE as a scalable, mutation-independent therapeutic platform with strong translational potential and substantial clinical reach for RHO-associated adRP.

Seasonal influenza A viruses cause significant global morbidity each year. Although vaccination remains the primary preventive strategy, effectiveness is often reduced by antigenic drift. This challenge is particularly pronounced for influenza A(H3N2), which has required eight vaccine updates over the past decade. Here, we present a computational framework to engineer broadly reactive influenza A(H3N2) vaccines, using protein language models to generate novel hemagglutinin (HA) sequences and a machine learning model to predict antigenic distance from circulating strains. In a proof-of-concept study, seven HA candidates designed using sequence data from 2013-2018 were evaluated in mice against contemporary and subsequently circulating viruses. Two candidates elicited protective levels of reactive antibodies, robust H3-specific antibody-secreting cell responses, and cross-neutralization against contemporary clades and drifted 2019-2020 strains. These findings demonstrate that an integrated generation-selection strategy can enhance vaccine coverage across current and future A(H3N2) seasons and may be applicable to other influenza subtypes.

Quorum sensing in Gram-positive bacteria commonly relies on posttranslationally modified peptide pheromones. In Bacillus subtilis, the prenyltransferase ComQ catalyzes tryptophan prenylation of the quorum-sensing peptide ComX, but the structural basis of this unique peptide modification has remained unclear. Here we identified a previously uncharacterized ComQ homolog, StheQ, and its cognate peptide substrate, StheX, from Sphaerobacter thermophilus and investigated their structural and functional relationship. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis demonstrated that StheQ catalyzes prenylation of the tryptophan residue located second from the C-terminus of StheX. Crystal structures of apo StheQ and its complexes with a farnesyl pyrophosphate analog revealed that StheQ adopts the all--helical fold of the trans-isoprenyl diphosphate synthase (IPPS) superfamily while possessing an active-site architecture adapted for peptide-based indole prenylation. The structures identified a single Mg2+-binding site associated with the first aspartic acid-rich motif and showed no evidence for metal coordination at the pseudo-second aspartic acid-rich motif. Site-directed mutagenesis, complex formation assays, and docking analyses identified a peptide-binding pocket adjacent to the active site and suggested that N215 contributes to productive positioning of the acceptor tryptophan. These findings establish the structural basis for peptide prenylation by a ComQ-family enzyme, providing insight into the evolution of peptide-based indole prenylation within the IPPS superfamily, and support the view that ComQ-family enzymes constitute a distinct functional branch specialized for peptide modification.

Scientific agents can produce plausible answers while remaining unable to establish whether the computation behind an answer is executable, recoverable, or reproducible. We present BloClaw, an AI4S workstation built around a simple principle: a scientific agent should know what it can do, show how it did it, and state what remains unvalidated. Each capability declares an execution state, input constraints, dependencies, expected outputs, and scientific limitations. Natural-language requests are translated into structured tasks, validated against this registry, executed through scientific tools, and recorded in a provenance-aware Living Lab Notebook. The system is designed to detect invalid inputs, failed tool calls, missing dependencies, and remote timeouts, and to route them to repair, retry, or escalation. The implemented and tested scope comprises RDKit-based molecular property and rule screening, protein structure analysis, docking-pose inspection, 3D visualization, and structured reporting. We demonstrate the workflow on a PubChem-retrieved osimertinib structure and a supplied 6LU7 docking artifact: the former yields deterministic descriptors (molecular weight 499.619 Da, cLogP 4.5098, TPSA 87.55 A^2), while the latter contains 2,387 protein ATOM records, 309 residues, and nine pose records. These examples are workflow demonstrations, not efficacy or affinity studies. Beyond retrospective prediction, the manuscript specifies a prior-minimized constructive mode in which a desired function is compiled into explicit physical, chemical, and systems constraints, candidate mechanisms are simulated, and observations are reintroduced for calibration and falsification; this is a proposed extension rather than a result of the present case studies. We describe an evaluation protocol that compares BloClaw with a standard single-agent workflow and fixed-script execution using task completion, scientific correctness, recovery success, provenance completeness, reproducibility, human review time, latency, and cost. This manuscript reports the system design, verified capability boundary, deterministic software artifacts, and a reproducible evaluation protocol; it does not claim benchmark improvements before those experiments are run. BloClaw is an execution and accountability layer for AI-assisted research, complementing expert review and experimental validation rather than replacing them.

Bacterial genome-wide association studies (GWAS) offer a powerful approach to identify the genetic basis of a trait measured in a set of sequenced isolates. As the number of sequenced isolates has grown, the limiting factor for GWAS has become phenotyping enough isolates to achieve statistical power. To overcome the need for large-scale phenotyping, we developed Bayesian Adaptive Sequential Sampling GWAS (BASS-GWAS), which couples Bayesian adaptive experimental design with a sparse regression model to select maximally informative isolates for phenotypic testing. BASS-GWAS efficiently recovered causal loci for three antimicrobial resistance traits in Neisseria gonorrhoeae, requiring many fewer phenotyped isolates than random sampling. We applied BASS-GWAS to discover variants enabling gyrBD429N-dependent cross-resistance to the novel topoisomerase inhibitors zoliflodacin and gepotidacin. After phenotyping fewer than 30 isolates, we identified and then validated both parCD86N and a gyrA-parE-based pathway as enabling cross-resistance. BASS-GWAS provides a practical and statistically principled solution for efficient bacterial GWAS.

Myxococcus xanthus bacteria form aggregates when starved on solid surfaces and some cells differentiate into spores. Studies of mutants in monoculture have advanced knowledge of this multi-cellular developmental process, but our understanding of the genetic determinants is incomplete. To assess gene function genomewide, we generated a pool of barcoded transposon insertion mutants, subjected it to starvation, and separated developmental samples into non-aggregated cells, aggregated cells, and spores. We also subjected our pool to chemically-induced unicellular sporulation. Evaluation of changes in the abundance of mutants in samples allowed identification of 200 genes in which insertions reproducibly caused distinct patterns of depletion and/or accumulation over time. Many of these genes have well-established roles in development, validating our approach, while many others have not previously been associated with development. Genes involved in type IV pili (T4P)-dependent motility were more important than gliding motility genes for aggregation and sporulation in the mixed population. Although exopolysaccharide (EPS) synthesis genes are required for aggregation in monoculture, most were dispensable for aggregation in our pool, consistent with EPS sharing between cells, yet these genes were required cell-autonomously for efficient sporulation. Genes for positive regulators of EPS synthesis were important for aggregation as well as sporulation, suggesting functions beyond EPS production. Insertions in several novel genes impaired both starvation- and chemically-induced sporulation. Many genes increased the efficiency of starvation-induced sporulation. Some of these mutants, which we call "developmental winners", are novel cheaters. Our results demonstrate the power of using the newly-created mutant library to elucidate M. xanthus biology.