Biology subjects

Zheng, Z.

Publications and source records attributed to Zheng, Z..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Scaling Personalized TMS: A Scalp-Based MRI-guided Alternative to Neuronavigation

BackgroundPersonalized transcranial magnetic stimulation (TMS) has shown promise in treating psychiatric and neurological disorders, but its accessibility is limited by reliance on costly and complex neuronavigation systems, particularly in resource-constrained clinical settings. ObjectiveTo develop and validate a scalp-based alternative to neuronavigation for personalized TMS targeting. MethodsWe developed a Continuous Proportional Coordinate (CPC) system-based approach for personalized TMS targeting and validated its performance through three operators across ten participants, using individualized DLPFC-SGC targets as an example. The validation framework included targeting consistency assessment, reproducibility evaluation, and cross-cortical generalizability analysis. ResultsThe CPC-based approach demonstrated comparable performance to neuronavigation, achieving 99.4% of its electric field strength (74.80 vs. 75.14 V/m; r = 0.962) and 93.9% of DLPFC-SGC functional connectivity (-0.216 vs. -0.230; r = 0.949), with high inter-operator reliability (ICC [≥] 0.903). Reproducibility analysis showed strong correlation between sessions (r = 0.948-0.957) with high reliability. Further simulations across 1,125 uniformly distributed cortical targets supported generalizability of this approach, with stable electric field preservation (99.07 {+/-} 1.54%) across different brain regions. ConclusionsThe CPC-based approach offers a practical alternative to neuronavigation, maintaining targeting accuracy and providing a more accessible option for personalized TMS implementation.

neuroscience↗

bioRxiv2025

Transcontinental Spread of HPAI H5N1 from South America to Antarctica via Avian Vectors

Our study has for the first time identified H5N1 strains (clade 2.3.4.4b, genotype B3.2) in brown skuas from the Fildes Peninsula, South Shetland Islands, Antarctica. These findings indicate that highly pathogenic avian influenza H5N1 viruses is now actively circulating in Antarctic ecosystems, representing a significant expansion of its geographic range.

genomics↗

bioRxiv2025

Guess till correct: Gungnir codec enabling high error-tolerance and low-redundancy DNA storage through substantial computing power

DNA has emerged as a compelling archival storage medium, offering unprecedented information density and millennia-scale durability. Despite its promise, DNA-based data storage faces critical challenges due to error-prone processes during DNA synthesis, storage, and sequencing. In this study, we introduce Gungnir, a codec system using the proof-of-work idea to address substitution, insertion, and deletion errors in a sequence. With a hash signature for each data fragment, Gungnir corrects the errors by testing the educated guesses until the hash signature is matched. For practicality, especially when sequenced with nanopore long-read, Gungnir also considers biochemical constraints including GC-content, homopolymers, and error-prone motifs during encoding. In silico benchmarking demonstrates its outperforming error resilience capacity against the state-of-art methods and achieving complete binary data recovery from a single sequence copy containing 20% erroneous bases. Gungnir requires neither keeping many redundant sequence copies to address storage degradation, nor high-coverage sequencing to address sequencing error, reducing the overall cost of using DNA for storage.

bioinformatics↗

bioRxiv2025

Disgust propensity, not disgust sensitivity, shapes the reactivity of a subjective disgust circuit in humans

Disgust constitutes an evolutionary adaptive defensive-avoidance response, yet humans vary markedly in their dispositional tendency to experience disgust (disgust propensity) and in their negative appraisal of such experience (disgust sensitivity). Conceptual frameworks and neuroimaging studies suggest that these traits may differentially modulate neural responses to disgust-eliciting stimuli; however, methodological constraints have left their precise roles unresolved. Our comparably large fMRI study (n = 142) therefore aimed to systematically determine how trait disgust modulates neural responses to carefully selected and validated disgust-specific visual stimuli across varying levels of subjective disgust experience. The whole-brain voxel-wise regression analyses revealed a neural dissociation between the two disgust traits, with disgust propensity, but not disgust sensitivity, modulating disgust-related neural activity in the anterior, middle, and posterior insula, as well as the caudate, putamen, thalamus, hippocampus, and parahippocampal gyrus. Mediation and network-level analyses further supported this dissociation by showing that disgust propensity shapes disgust experience via insula - striatal - hippocampal pathways. Together, these findings provide evidence for a neurofunctional dissociation of disgust propensity and sensitivity and elucidate how trait disgust shapes subjective experiences. They further suggest that disgust propensity and the identified systems may represent promising targets for the regulation of disgust-related pathology.

neuroscience↗

bioRxiv2025

Novel Predictive Spatial Biomarker in Non-Small Cell Lung Carcinoma: The Diversity of Niches Unlocking Treatment Sensitivity (DONUTS)

Probabilistic spatial modelling techniques developed on large-scale tumor-immune Atlases ([~]35M individually mapped cells; 50,000 high power fields) were used to characterize predictive features of treatment-responsive lung cancer. We identified CD8+FoxP3+ cell density as a robust pre-treatment biomarker for outcomes across disease stages and therapy types. In parallel, single-cell RNAseq studies of CD8+FoxP3+ T-cells revealed an activated, early effector phenotype, substantiating an anti-tumor role, and contrasting with CD4+FoxP3+ T-regulatory cells. A spatial biomarker was developed using an empirical probabilistic model to define the immediate cell neighbors or niche surrounding CD8+FoxP3+ cells and proximity to the tumor-stromal boundary. The resultant Diversity of Niches Unlocking Treatment Sensitivity (DONUTS) are more prevalent than the CD8+FoxP3+ cells themselves, mitigating sampling error in small biopsies. Further, the DONUTS only require four markers, are additive to PD-L1, and associate with tertiary lymphoid structure counts. Taken together, the DONUTS represent a next-generation predictive biomarker poised for clinical implementation. HIGHLIGHTSO_LILarge-scale tumor-immune Atlases drive robust computational biomarker development C_LIO_LICD8+FoxP3+ cells are anti-tumor T-cells and predict response to therapy C_LIO_LIThe niches or spatial donuts around CD8+FoxP3+ cells boost biomarker performance C_LIO_LICD8+FoxP3+ donuts are hallmarks of a larger immune organization that includes TLS C_LI

pathology↗

bioRxiv2025

Advancing Target Discovery Through Disease-Specific Integration of Multi-Modal Target Identification Models and Comprehensive Target Benchmarking System

Target identification is crucial for drug development. AI-driven approaches leveraging multi-omics and computational modeling can accelerate this process. However, integrating multi-modal data for disease-specific target identification and predicting translational potential remains challenging. Moreover, the absence of a systematic evaluation framework for model performance limits confidence in target reliability. We present a unified platform combining machine learning-based target identification with comprehensive benchmarking. As a testbed, we developed Target Identification Pro (TargetPro), a disease-specific model spanning 38 diseases across oncology, metabolic, immune, fibrotic, and neurological categories. TargetPro shows strong predictive performance for clinical-stage targets and reveals disease-specific patterns, underscoring the need for tailored target detection models. We next created Target Identification Benchmark (TargetBench 1.0) to rigorously assess target identification systems, including large language models, based on their ability to recover established targets and find high-quality novel candidates. This integrated approach offers a streamlined strategy to evaluate target discovery models, ultimately improving drug development efficiency.

bioinformatics↗

bioRxiv2025

Dorsal Attention Network as a Convergent Hub of Diverse Non-pharmacological Interventions Preserving Functional Gradients and Cognition in Aging

Non-pharmacological interventions (NPIs) in aging neuroscience have largely focused on intervention-specific regional effects, with limited understanding of generalizable network-level mechanisms. Here, adopting a previously unexplored gradient-based perspective of functional brain organization, we analyzed an NPI dataset involving four interventions in older adults (training/control group: n = 112/59). NPIs led to strengthened intra-network functional integration and maintained macroscale gradient architecture. Virtual lesion analyses identified the dorsal attention network (DAN) as a key contributor to gradient maintenance. Critically, enhanced post-intervention DAN connectivity was associated with maintained gradient structure and improved global cognition. These findings establish a unifying framework in which the DAN acts as a convergent hub through which diverse NPIs preserve functional brain organization and attenuate cognitive aging.

neuroscience↗

bioRxiv2025

Functional screening of TCR-like antibodies for targeted cancer immunotherapy

Although hybridomas and display technologies have long been used in antibody discovery, identifying TCR-like antibodies that recognize major histocompatibility (MHC)-presented neoantigens remains an inefficient process. Here, we present a functional screening approach for antibody discovery based on T cell-specific functionality. By constructing Synthetic T cell receptor and Antigen Receptor (STAR)-T cells expressing antibody libraries and co-culturing them with target cells, we observed distinct antigen-specific STAR endocytosis and T cell activation. These two indicators are combined into an E-A functional index, which we demonstrate as an effective screening strategy for identifying antibodies with strict antigen sensitivity and specificity. Using this E-A functional screening method, we successfully discovered antibodies or nanobodies targeting cell-surface tumor antigens and neoantigens presented by human leukocyte antigen (HLA). These antibodies exhibited potent anti-tumor efficacy both in vitro and in vivo. Moreover, converting these antibodies into chimeric antigen receptors (CARs) and bispecific antibodies also induced T cell activation and tumor killing. In summary, our study establishes a robust functional screening strategy for identifying antibodies or TCR-like nanobodies targeting tumor-specific neoantigens, offering significant potential for advancing targeted cancer therapies.

immunology↗

bioRxiv2025

Investigating the sensitivity of the diffusion MRI signal to magnetization transfer and permeability via Monte-Carlo simulations

PurposeMagnetization transfer (MT) and water exchange via permeability operate on a similar spatiotemporal scale to water diffusion. In this study, we use a simulation-based approach to characterise how MT and permeability impact (1) diffusion-weighted MRI (dMRI) measurements from cylindrical substrates and (2) parameter estimation using a two-compartment model of white matter. MethodsWe used Monte-Carlo simulations to model the dMRI signal inside and outside axons by simulating signals from parallel cylinders with different diameters and volume densities. We subsequently introduced membrane permeability and MT at the cylinder walls to investigate their impact on the dMRI signal. We fitted a two-compartment model to the simulated signal to produce estimates of the cylinder diameter and density. We evaluated the impact of MT and permeability by comparing the fitted diameter and density to the simulated ground truth. ResultsPermeability leads to underestimation (up to 100%) of cylinder diameter and density. Specifically, by enabling isochromats to escape from restrictions and diffuse more freely, permeability makes the overall displacement profile closer to the extra-axonal displacement profile. MT had limited effects on diameter estimation but caused substantial bias (20-50%) in volume density estimates depending on the ratio of the intra-axonal and extra-axonal volume fraction. This is due to the intra-axonal and extra-axonal space having different surface-to-volume ratios and therefore different surface relaxation rates. ConclusionPermeability and MT can considerably influence the dMRI signal. They increase the relative contribution from larger cylinders to the dMRI signal and bias microstructural parameter estimates derived from dMRI data.

neuroscience↗

bioRxiv2025

Connectomic reconstruction from hippocampal CA3 reveals spatially graded mossy fiber inputs and selective feedforward inhibition to pyramidal cells

The mossy fiber (MF) connections to pyramidal cells in hippocampal CA3 are hypothesized to participate in pattern separation and memory encoding, yet no large-scale neuronal wiring diagram exists for these connections. We assembled a 3D electron microscopy volume ([~]1x1x0.1mm3) from mouse hippocampal CA3. By proofreading and automated segmentation, we reconstructed and classified all soma-containing neurons--including 1,815 pyramidal cells and 229 inhibitory cells--and over 55,000 MFs. Pyramidal cells receive more numerous MF inputs along a proximodistal gradient. Some distal cells show surprisingly high convergence via relatively small terminals with fewer vesicles. Pyramidal cells share significantly more MF inputs than networks randomized by degree-preserving swap, and are better approximated by networks randomized by proximity-preserving swap. We identify a feedforward inhibitory circuit from MFs via perisomatic interneurons that selectively target a pyramidal subtype. We demonstrated large-scale mapping across levels in the hippocampus--from circuits to cell types to vesicles. The dataset is shared through Pyr, an online platform for hippocampal connectomics.

neuroscience↗

bioRxiv2025

StruCloze: A Unified Framework for Backmapping and Inpainting of Biomolecules

Atomistic resolution is essential for understanding biomolecular structure and function, yet coarse-grained (CG) models remain indispensable for simulating large and dynamic systems. Reconstructing accurate all-atom structures from CG representations, particularly across varied CG schemes and biomolecular types, remains a fundamental challenge. Moreover, flexible or disordered regions may well suffer from failure in structure modeling, making inpainting missing regions another challenging task. Here, we present StruCloze, a deep learning framework for reconstructing atomistic structures from CG models and inpainting missing regions for both proteins and nucleic acids. StruCloze generalizes across various CG levels and biomolecule types on single pretraining, with minimal fine-tuning required for optimal performance on specific representations. It achieves state-of-the-art accuracy in reconstructing both protein and nucleic acid structures, demonstrates superior transferability and speed compared to existing methods. Leveraging masked learning strategy, StruCloze also excels at inpainting structurally missing regions in structures, offering a practical tool for structural refinement and integrative modeling. Our framework provides a general solution for bridging reduced or incomplete representations with full atomistic detail of biomolecular structures, enabling rapid local structure prediction and further analysis on system dynamics.

bioinformatics↗

bioRxiv2025

Reprogramming of Cellular Plasticity via ETS and MYC Core-regulatory Circuits During Response to MAPK Inhibition in BRAF-mutant Colorectal Cancer

BackgroundAberrant enhancer dynamics play a critical role in the initiation and progression of colorectal cancer (CRC). BRAFV600E-mutated metastatic CRC may be a unique subtype, exhibiting a strong epigenetic phenotype. Interestingly, bromodomain 2, a reader protein for H3K27ac-marked enhancers, was found to be synthetically lethal in CRC with BRAF + EGFR inhibition. DesignWe evaluated the effectiveness of targeting aberrant enhancers with bromodomain and extraterminal (BET) + MAPK pathway inhibitors in patient-derived xenograft models of metastatic CRC, followed by comprehensive profiling of transcriptomic and chromatin dynamics upon BET inhibitor combination treatment. ResultsThe combination of BET and standard MAPK inhibitors has demonstrated improved efficacy against BRAFV600E CRC and selective improvements against RAS-mutant CRC in vivo. We showed that BET + MAPK inhibition induced a profound downregulation of the MAPK signaling pathway compared to MAPK inhibition alone. The loss of activation signal on enhancers, as determined by H3K27ac, led to dysregulation of core-regulatory circuitries of CRC, especially loss of the auto-regulatory mechanism of the MAPK downstream E26 transformation-specific transcription factor family. Single nucleus multiome (RNA + ATAC) sequencing further distinguished differential transcriptomic and chromatin dynamics at cell type levels. Profound downregulation of well-differentiated cell types confirmed deep inhibition of MAPK signaling and downstream transcription factors. On the other hand, dedifferentiated cell populations were abundant after MAPK or combination inhibition, suggesting therapy-induced cell state switching and adaptation. ConclusionWe are evaluating BET + BRAF + EGFR inhibition in patients with treatment-refractory BRAFV600E metastatic CRC. ClinicalTrial.gov identifier: NCT06102902. What is already known on this topicEnhancer aberrations emerge as critical epigenetic features in the progression of colorectal cancer (CRC). However, the dynamics of active enhancer and the therapeutic potential of enhancer blockade, particularly in CRC tumors with BRAFV600E mutation, is not well understood. What this study addsThis study demonstrates improved efficacy of BET inhibitor combination therapies in diverse patient-derived models and reveals epigenetic reprogramming driven cellular plasticity in BRAFV600E-mutated CRC. How this study might affect research, practice or policyOur findings support treatment with BET + BRAF + EGFR inhibitors for patients with BRAFV600E-mutant mCRC [NCT06102902]. This study also highlights the potential of combining epigenetic agents to standard targeted therapy, offering a novel treatment option for this subset of patients.

cancer biology↗

bioRxiv2025

SR9009 Regulates Macrophage Polarization via the NR1D1/NF-κB Axis to Ameliorate Obesity Associated Ulcerative Colitis

ObjectiveThe incidence of ulcerative colitis (UC) and obesity has risen in recent years, potentially linked through metabolic dysregulation and chronic inflammation. The nuclear receptor NR1D1 is pivotal in regulating circadian rhythms and plays a significant role in inflammation and metabolism. This study investigates the therapeutic effects and mechanisms of the NR1D1 agonist SR9009 on obesity-related UC. MethodsWe established a mouse model of obesity-induced UC utilizing a high-fat diet alongside dextran sulfate sodium (DSS). 32 male C57BL/6 mice were divided into four groups: control (DZ), high-fat diet (GZ), obesity associated UC model group (UC), and SR9009 intervention group (JD), with eight mice each. We evaluated body weight, blood lipids, colonic tissue alterations, IL-1{beta}, IL-18, macrophage polarization, and NR1D1 expression levels. ResultsMice in the UC group demonstrated significantly elevated body weight, spleen index, TG, CHOL and inflammatory markers (P<0.01). Pathological scores of colonic tissues increased markedly (P=0.000), with a rise in M1 macrophages (CD68) and a decline in M2 macrophages (CD206) (P<0.001). NR1D1 expression was notably downregulated (P<0.01). Post-SR9009 intervention, the JD group showed significantly reduced serum TG and CHOL levels (P=0.001, 0.011), IL-1{beta} and IL-18 (P<0.001), improved colonic pathology (P=0.000), a decrease in M1 macrophages, an increase in M2 macrophages, and an enhanced M1/M2 ratio (P<0.001). ConclusionSR9009 mitigates intestinal inflammation in obesity associated UC by activating NR1D1, inhibiting the NF-{kappa}B pathway, and modulating macrophage polarization (suppressing M1 and enhancing M2). These findings propose a novel strategy for targeting NR1D1 in the treatment of obesity-related ulcerative colitis.

molecular biology↗

bioRxiv2025

DynaRNA: Dynamic RNA Conformation Ensemble Generation with Diffusion Model

RNA plays a wide variety of roles in biological processes. In addition to serving as the coding messenger RNA (mRNA), the vast majority of RNAs function as non-coding RNAs (ncRNAs), where their dynamic structural ensemble is critical for mediating diverse biological functions. However, traditional experimental techniques and molecular dynamics (MD) simulations face significant challenges in characterizing the conformational dynamics of RNA, due to inherent methodological limitations and high computing power cost. We herein presented DynaRNA, a diffusion-based generative model for RNA conformation ensemble. DynaRNA employs denoising diffusion probabilistic model (DDPM) with equivariant graph neural network (EGNN) to directly model RNA 3D coordinates, enabling rapid exploration of RNA conformational space. DynaRNA enables end-to-end generation of RNA conformation ensemble reproducing experimental geometries without the need for Multiple Sequence Alignments (MSA) information. Our results demonstrate that DynaRNA effectively and accurately generate tetranucleotides ensemble with lower intercalation rate than molecular dynamics simulations. Besides, DynaRNA has the ability to capture rare excited states of HIV TAR(trans-activation response) element, and recapitulate de novo folding of tetraloops. DynaRNA serve as a versatile and efficient platform for modeling RNA structural dynamics, with broad implications potential in RNA structural biology, synthetic biology, and therapeutic development.

bioinformatics↗

bioRxiv2025

Neurocomputational Mechanisms Linking Future Interaction Prospects to Reactive and Proactive Costly Punishment

Costly punishment within social bonds manifests as both reactive penalties for transgressions and proactive sanctions against fair behaviors, yet a unified neurocomputational framework remains elusive. Combining neuroimaging and computational modeling, this study examined how future interaction prospects--a key element of social bonds--modulate reactive and proactive punishment. Participants acted as second- or third-party punishers, responding to allocation offers from individuals with or without future interactions. Results showed that participants imposed harsher punishment on both fair and unfair offers from individuals they did not expect to interact with, aligning with lower self-reported social closeness. Heightened provocation sensitivity, reflected in dorsal anterior cingulate cortex activity, drove the increased reactive punishment toward wrongdoers without future interactions, whereas punishment of future-interacting transgressors was associated with enhanced dorsolateral and dorsomedial prefrontal cortex (dlPFC, dmPFC) activity. A stronger preference for relative advantage and reduced harm sensitivity, linked to dlPFC and temporoparietal junction activity, mediated greater proactive punishment towards non-future-interacting individuals. Moreover, proactive punishment and underlying neurocognitive processes followed a collective retaliation pattern, increasing after unfair (vs. fair) behavior from another non-future-interacting individual. These findings establish a unified neurocomputational framework for understanding how future interaction prospects regulate costly punishment, integrating reactive and proactive motives within social bonds.

neuroscience↗

bioRxiv2025

Lipid nanoparticle-mediated CRISPR/Cas9 delivery enables efficient trabecular meshwork gene editing in mice

Lipid nanoparticles (LNPs) have emerged as a transformative platform for mRNA delivery, enabling vaccines and gene editing with transient expression and high cargo capacity. However, their potential for ocular gene editing remains underexplored. In this study, we assessed the transduction efficiency, inflammatory response, and gene editing capability of LNP-encapsulated mRNA in murine eyes. Intravitreal delivery of LNPs achieved targeted mRNA expression in the trabecular meshwork (TM) with superior specificity and efficiency compared to adenoviral or adeno-associated viral vectors, while inducing minimal microglial activation in the retina. Using LNPs co-encapsulating SpCas9 mRNA and sgRNA, we demonstrated efficient CRISPR-mediated knockout (KO) of Matrix Gla Protein (Mgp), a key inhibitor of TM calcification. Mgp-KO eyes exhibited sustained intraocular pressure (IOP) elevation and anterior chamber deepening with normal anterior chamber angle, recapitulating key features of primary open-angle glaucoma (POAG). Chronic IOP elevation led to reactive Muller gliosis and ganglion cell complex thinning, reflecting retinal stress and progressive neurodegeneration. Our findings establish LNP-CRISPR as a safe and efficient system for TM-targeted gene editing, with broad applicability in glaucoma pathogenesis modelling and therapeutic discovery.

neuroscience↗

bioRxiv2025

Neural signature underlying the effect of intranasal vasopressin on emotional responses to spontaneous social comparison

Vasopressin, a key molecular regulator of social behavior, is implicated in promoting self-protective responses to threats against physical safety and resources. However, its role in defending against self-view threats--common in social interactions and critical to well-being--remains unclear. This study investigates the neural mechanisms through which vasopressin modulates self-protective responses to spontaneous social comparison. In a double-blind, placebo-controlled neuroimaging experiment, participants rated their satisfaction with social evaluations and monetary outcomes assigned to a stranger, friend, or themselves. Compared to placebo, vasopressin selectively intensified contrastive emotional responses to social evaluations of the stranger, decreasing satisfaction with positive evaluations and increasing satisfaction with negative evaluations, relative to those of the self or friend. At the neural level, vasopressin reduced the distinctions between the stranger and the self/friend in the medial prefrontal cortex activity, multivariate response patterns, and functional connectivity with the temporoparietal junction and precuneus, with this effect being especially pronounced among socially dominant individuals. These converging neuroimaging findings support the hypothesis that vasopressin alters the neural representation of the stranger, shifting it from a socially irrelevant figure under placebo to a psychologically salient competitor, thereby triggering self-protective emotional processes. These findings elucidate novel neuropsychological mechanisms through which vasopressin amplifies emotional defense against social threats and offer insights into potential clinical applications for psychiatric conditions characterized by impaired self-protection.

neuroscience↗

bioRxiv2025

A synthetic biology toolkit for interrogating plasmid-dependent methylotrophy and enhancing methanol-based biosynthesis of Bacillus methanolicus

Bacillus methanolicus represents a thermophilic methylotroph whose methanol utilization depends on plasmid-encoded genes. It serves as a unique model for deciphering plasmid-dependent methylotrophy and an ideal chassis for low-carbon biomanufacturing using CO2-derived C1 substrates. Despite its evolutionary uniqueness and industrial potential, the lack of synthetic biology tools has hindered both mechanistic understanding and strain engineering. Here, we present a comprehensive synthetic biology platform comprising a high-efficiency electroporation protocol, a CRISPR method enabling robust and multiplex genome editing, diverse neutral loci for gene integration and overexpression, and a cloud-based genome-scale metabolic model iBM822 for user-friendly biodesign. Leveraging this toolkit, we systematically dissected plasmid-dependent methylotrophy, host restriction-modification systems, and functional significance of the chromosomal methylotrophic genes through targeted deletion. To address plasmid loss-induced strain degeneration, we integrated the large endogenous plasmid pBM19 into the chromosome for stable and intact methylotrophic growth. Finally, by integrating metabolic modeling with CRISPR editing, we engineered L-arginine feedback regulation to achieve the first L-arginine biosynthesis from methanol. This study establishes a synthetic biology framework for B. methanolicus, promoting mechanistic exploration of methylotrophy and low-carbon biomanufacturing.

synthetic biology↗