SEARCH · bioRxiv Science

Results for “synthetic biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

95 recordsLinked to original sources

bioRxiv2026

Harnessing Escherichia coli motility to engineer bacterial Voronoi patterns

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.

synthetic biology↗

bioRxiv2026

Uncertainty Quantification in Stochastic Dynamical Gene Regulatory Networks

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.

synthetic biology↗

bioRxiv2026

Rclade: automated taxonomic collapsing and geological-timescale annotation of time-calibrated phylogenetic trees in R

Background: Reproducible taxonomic collapsing and geological-timescale annotation of time-calibrated phylogenetic trees in R often require coordination among several packages and repeated code for label parsing, clade validation, plotting, and export. Workflow-managed analyses additionally benefit from non-interactive configuration, predictable diagnostics, and machine-readable exit status. Results: We present Rclade, an R package that consolidates the multi-package coordination required for taxonomic collapsing into a streamlined, single-function interface. Rclade provides (1) custom ggproto objects (GeomPolygonStraight/GeomSegmentStraight) that bypass coord_munch() interpolation to achieve straight-edge rendering of collapsed triangles in circular layouts; (2) automatic detection and parsing of four taxonomic-label formats (GTDB, Silva, NCBI, embedded) plus user-supplied custom regex, with explicit input-validation contracts and parsing-accuracy evaluation on real and derived test sets; and (3) workflow embeddability through YAML configuration, library-mode APIs, and standard Unix exit codes. Benchmarks on synthetic and real datasets (200-10,000 synthetic tips and real reference trees up to 10,122 tips; 5 replicates at every scale under a unified fully rendered measurement protocol) show that the full-pipeline overhead is modest for interactive use (median {approx}0.87 s in-session rendering and {approx}8.4 s process-level wall-clock at 10,000 tips). Conclusions: Rclade is a convenience layer over the ggtree/deeptime ecosystem that reduces boilerplate while adding targeted technical improvements for circular-layout rendering and format heterogeneity management.

bioinformatics↗

bioRxiv2026

Resolving Heterogeneous Mechanical Domains via Physics-Aware Deep Clustering of Single-Molecule Force Spectroscopy Data

Many biological processes rely on mechanical forces, with protein molecules acting as key mediators. Understanding how proteins respond to mechanical stress is essential for conditions including cardiomyopathy and muscular dystrophy. Natural proteins such as dystrophin and utrophin are composed of heterogeneous folding domains with distinct mechanical properties; deciphering domain-level behavior provides insights into disease mechanisms and informs therapeutic strategies. Single-molecule force spectroscopy (SMFS) enables probing the mechanical properties of entire proteins, yet current approaches struggle to identify heterogeneous folding domains, particularly without prior knowledge. Here, we present the first automated framework to identify heterogeneous folding domains in SMFS data, applying both existing clustering methods and a novel physics-aware deep clustering architecture, LatentUnfold. LatentUnfold learns complementary latent representations from force magnitude and the force-extension physical relationship through dual autoencoders, jointly optimized for clustering assignments. We apply our framework to experimental SMFS data collected from a synthetic two-domain protein (ddFLN4-Titin I27) as well as natural protein constructs of dystrophin and utrophin, with Monte Carlo simulated datasets serving as controlled validation. For the synthetic protein, we recover mechanical properties consistent with previously reported values for each domain. For the natural proteins, we uncover two mechanically distinct domain populations - corresponding to the N-terminal domain and spectrin-like repeats - with differences in both unfolding force and contour length increase, and reveal different unfolding order between them for the first time. This work enables domain-level biological inference, overcoming prior limitations that relied on averaging and overlooked heterogeneity, thus advancing the understanding of mechanical behavior in protein unfolding.

biophysics↗

bioRxiv2026

3D ultrasound fascicle tractography for objective muscle architecture analysis.

Muscle architecture shapes muscle function and changes with age, growth, training and disease, yet quantifying three-dimensional (3D) muscle architecture in vivo remains challenging. We introduce a hybrid fascicle tractography approach for freehand 3D ultrasound data that accurately reconstructs 3D muscle fascicles with respect to an objective, anatomically relevant coordinate system defined by the muscle's central aponeurosis. The hybrid approach combines Hessian-based fascicle detection with wavelet-based refinement to generate volumetric fascicle orientations. In a synthetic dataset with known ground truth, fascicle orientations and lengths were estimated with errors of [≤]2{degrees} and ~1.5%, respectively. In vivo, the approach detected physiologically plausible fascicle lengthening in the human tibialis anterior following a passive plantar flexion rotation, whereas diffusion tensor imaging of the same muscle did not. The proposed method enables anatomically relevant, objective and non-invasive quantification of 3D muscle architecture in vivo, providing a practical framework for applications in clinical and applied muscle physiology.

bioengineering↗

bioRxiv2026

A reproducibility-audit framework for generalizable versus dataset-specific molecular transition boundaries in Alzheimer's disease

Molecular staging of Alzheimer's disease (AD) increasingly defines transition boundaries along single-cell pseudo-progression trajectories, yet whether such boundaries reproduce across brain regions, cohorts and molecular modalities is rarely tested. We present a permutation-controlled audit that combines nine boundary-detection algorithms with a fixed marker panel and four orthogonal reproducibility axes-algorithmic consensus, region, cohort and modality. On synthetic data with planted ground-truth boundaries the audit reaches 100% sensitivity and 94% specificity, rejecting four distinct artefact classes each by a different axis. Applied to the Seattle Alzheimer's Disease Brain Cell Atlas middle temporal gyrus, it localizes a transition that is robust across algorithms and recovered in most cell types but does not generalize: its leading marker is attenuated or absent in prefrontal cortex, entorhinal cortex and cerebrospinal fluid, and an apparent cross-region conservation of glial metabolic genes proves to be a global-expression offset rather than a shared program. The same audit nonetheless certifies an externally validated marker (astrocytic PTGDS) as reproducible across regions and modalities, showing that it separates generalizable anchors from dataset-specific ones rather than rejecting all signals. We provide this four-axis audit as a transferable, code-available standard to apply before a trajectory boundary is read as a biological stage, in AD and other progressive proteinopathies.

neuroscience↗

bioRxiv2026

Cryo-EM Structure of a Triazole alpha-Conotoxin GI Mimetic Bound to the Muscle-Type Nicotinic Acetylcholine Receptor

Disulfide-rich peptides possess exceptional potency and selectivity but are often limited by the instability and synthetic challenges associated with native disulfide bonds. Here, we report the design, synthesis, pharmacological evaluation, and structural characterisation of triazole-based peptidomimetics of the -GI conotoxin, a selective antagonist of the muscle-type nicotinic acetylcholine receptor (nAChR). A series of 1,4- and 1,5-disubstituted triazole analogues were prepared entirely on resin using CuAAC and RuAAC chemistry to replace the native Cys3/13 disulfide bridge. Functional evaluation against human muscle nAChRs revealed that 1,5-triazole analogues retained low-nanomolar potency, with the lead mimetic exhibiting activity comparable to native -GI. Cryo-electron microscopy of the lead compound bound to the muscle-type nAChR provided the first structure of a disulfide-isostere peptidomimetic in complex with a membrane receptor. The structure demonstrates that the 1,5-triazole reproduces the native peptide fold with high fidelity while contributing receptor-facing interactions not available to the native disulfide bridge. Molecular dynamics simulations further revealed conserved hydration networks and similar conformational sampling between the native peptide and lead mimetic. Together, these findings establish triazoles as effective disulfide surrogates and provide a structural framework for the rational design of stabilised conotoxin therapeutics.

biochemistry↗

bioRxiv2026

Intelligent differential ion mobility spectrometry (iDMS): A deep neural network that predicts optimal space-resolved ion mobility parameters for isomeric monoglycosphingolipids

Simultaneous quantification of monoglycosphingolipid stereoisomers is required to monitor changes in defective enzymatic pathways linked to diseases such as Gaucher Disease, Parkinson's Disease, and Krabbe Disease. Resolution of beta-glucosyl and beta-galactosyl epimers cannot be achieved by standard liquid chromatography, electrospray ionization, tandem mass spectrometry (LC-ESI-MS/MS). Separation becomes possible when field asymmetric ion mobility spectrometry (FAIMS), also known as differential mobility mass spectrometry (DMS), is added as an orthogonal separation technique to LC. FAIMS/DMS separates epimeric ion clusters in a high versus low electric field (separation voltage, SV) then redirects the target epimeric ions to the mass spectrometer through the application of a direct current (compensation voltage, CoV). Resolving SVs and CoVs must be manually determined for each lipid. Manual derivation is a labour-intensive process that requires pure synthetic standards, limiting the number of stereoisomers a user can include in an assay. To address this problem, we introduce here intelligent DMS (iDMS). iDMS is an in silico supervised neural network model that learns the ion mobility relationships between SV and CoV and the monoglycosphingolipid structural features of sugar headgroup, N-acyl chain length, and N-acyl degree of unsaturation. iDMS predicts the SV and CoV combinations capable of resolving any stereoisomer pair from a training dataset of composed of measured signal intensities across a range of SVs and CoVs of 12 lipids. This machine learning alternative to manual DMS optimization promises to accelerate the deployment of multiple-reaction-monitoring mode (MRM) RPLC-ESI-DMS-MS/MS assays for the routine and rapid quantification of biologically relevant monoglycosphingolipid stereoisomers.

bioinformatics↗

bioRxiv2026

From Prompt to Provenance: BloClaw, a Capability-Gated AI4S Workstation for Auditable Computational Biology

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.

bioinformatics↗

bioRxiv2026

Three new species of Thelymitra (Diurideae, Orchidaceae) endemic to Aotearoa New Zealand.

Three new species of sun orchid (Thelymitra) endemic to Aotearoa New Zealand are here described. These are T. palustris, T. scabrifolia and T. semaphora. The morphological distinctiveness of these three species has been acknowledged for decades; however, their taxonomic status has remained unresolved. Evidence from existing karyological data, recently generated DNA sequence data (LFY and ycf1) and morphological studies from historical and fresh collections are used here to support their formal description. Both, T. palustris and T. semaphora are restricted to wet habitats north of Auckland (North Island). Thelymitra scabrifolia inhabits mostly scrub, and it has a similar northern North Island distribution, but is has been found also in Manawat[a]whi / Three Kings Islands and historically in Otago (South Island). All three species are polyploids and are of conservation concern.

plant biology↗

bioRxiv2026

Nitrate regulates anchor root development

Nitrogen is a critical nutrient necessary for plant growth and survival. Plasticity in root architecture helps adapt to soil nitrogen levels for optimal nitrogen uptake; the nitrate form of soil nitrogen is a major modulator of root architecture. Although details of nitrate-regulated primary and lateral root growth are known, nitrate-regulated formation of anchor roots, which arise from the collet, is not understood. In this work, we uncover a role for nitrate in the regulation of anchor root formation. We find that cytokinin inhibits anchor root formation with rising nitrate. These cytokinin effects on anchor root formation rely on regulated indole-3-butyric acid (IBA) to indole-3-acetic acid (IAA) conversion. These data point toward a mechanism by which nitrate controls a previously underappreciated aspect of nitrate-dependent root architecture driven by anchor roots.

plant biology↗

bioRxiv2026

Starvation improves epithelial fitness by selectively extruding DNA damaged cells

During homeostasis, crowded cells with the lowest energy levels are eliminated by extrusion via Piezo1 signalling to maintain constant cell numbers. However, crowding-induced extrusion does not necessarily remove damaged or otherwise unfit cells. Here, we show that glucose or glutamine starvation triggers a rapid, regulated wave of extrusion, called starvation-induced cell extrusion (STICE), that selectively eliminates cells bearing DNA damage markers via a p53-dependent, Piezo1-independent pathway, improving monolayer fitness. Unlike non-extruding cells, which recycle contents through autophagy and lysosomal digestion, p53-activated cells instead use LC3 to drive lysosomal exocytosis, promoting extrusion signalling. By eliminating defective and transformed cells, STICE confers resistance to damage and apoptotic stimuli in the remaining monolayer. STICE thus acts as a tissue-level analogue of autophagy: rather than improving individual cells by digesting and recycling damaged components, it improves tissue fitness by eliminating substandard cells.

cell biology↗

bioRxiv2026

Extracellular Vacuole-derived bodies (EVacs) mediate RNA secretion in plants

Extracellular RNAs are found in the plant extracellular space, but how they are exported from cells remains unclear. We found that the plant vacuole is a major source of extracellular RNA and identified a class of large extracellular vacuole-derived bodies, which we termed EVacs, that are key mediators of this transport. EVacs are marked by the vacuolar membrane (tonoplast) proteins {gamma}-TIP and V-ATPase and originate as intravacuolar structures formed by inward folding of the tonoplast, encapsulating intact cytoplasmic material, including both RNAs and proteins. These intravacuolar bodies then escape the vacuole and are subsequently released from the plasma membrane of mesophyll cells into the apoplast. These findings provide a novel mechanism for the unconventional secretion of macromolecules in plants.

plant biology↗

bioRxiv2026

PRISM: A Plasmid-based Reporter for Intracellular Spectral Microscopy

Organelles form an interconnected network whose morphology, positioning and interactions reflect cellular state. However, reproducibly quantifying these organelle phenotypes across large cell populations and diverse cell types remains a significant challenge. Here we present PRISM (Plasmid-based Reporter for Intracellular Spectral Microscopy), a PiggyBac-integrable construct encoding five unique fluorescent organelle reporters for spectral microscopy, with an accompanying modular analysis pipeline. PRISM stably labels the Golgi, peroxisomes, endoplasmic reticulum, mitochondria and lysosomes in multiple cell types while remaining compatible with additional molecular or functional probes. The workflow extracts over 500 metrics per cell, describing organelle morphology and distribution alongside pairwise and higher-order contacts. We use PRISM to characterise organelle responses to cytoskeletal perturbation, map PI(4)P redistribution during lysosomal damage, and reveal how Zika virus remodels the organelle landscape during infection. PRISM provides a reproducible approach for investigating organelle network remodelling across biological contexts

cell biology↗

bioRxiv2026

An ancestral pronephric contribution reveals the multilineage origin of the teleost gonad and revises the evolution of vertebrate gonadogenesis

Challenging the paradigm that pronephric field contribution to gonadal formation would be an amniote innovation, we demonstrate this trait is ancestral to bony vertebrates. Using cell lineage tracing, single-cell and spatial transcriptomics, and functional validation, we show that the teleost gonad arises from three distinct embryonic tissues, the pronephros, the coelomic epithelium, and the lateral plate mesoderm, in contrast to amniotes. This multi-tissue origin generates an unexpected lineage-based cellular diversity. Further cross-species comparisons over medaka, mouse, chicken and turtle unravel how lineage-specific deviations shape early gonadal development. Specifically, we map these variations amongst the different gene regulatory networks, outlining their physiological implications for specialized gonadal functions. Our results support a model in which heterochronic shifts are coupled to regulatory rewiring of conserved gene networks, driving lineage-specific developmental trajectories through a canalized developmental system drift.

developmental biology↗

bioRxiv2026

Activation and inactivation pathways of a p53-like transcription factor govern lipid homeostasis in yeast

Membrane fluidity depends on unsaturated acyl chains that are generated in Saccharomyces cerevisiae by the desaturase Ole1, whose expression is primarily under the control of the transcription factor Mga2. Here, we show that the endoplasmic reticulum-anchored Mga2 precursor is ubiquitinated by the E3 ligase Rsp5 and then processively degraded by the proteasome until proteolysis stalls at a defined site, releasing a soluble fragment that enters the nucleus and activates Ole1 transcription. Unexpectedly, Mga2 contains a DNA-binding domain and a trans-activation-like segment structurally and functionally related to those of the human tumor suppressor p53. The mature transcription factor is degraded in the nucleus in a DNA binding-dependent manner; blocking this degradation causes unsaturated acyl chains to accumulate in lipid droplets, a detoxification response required for cell viability. These findings define the pathways that activate and inactivate Mga2, and uncover an evolutionary connection between the yeast lipid homeostasis regulator Mga2 and p53.

cell biology↗

bioRxiv2026

Subcellular carbohydrate compartmentation and organic acid signatures reveal natural variation in cold acclimation of Arabidopsis thaliana

Plant cold acclimation emerges from coordinated adjustments in photosynthesis, primary metabolism, and intracellular carbon allocation. Yet, the regulatory role of subcellular metabolite compartmentation in natural variation of cold acclimation remains insufficiently understood. Here, we investigated four Arabidopsis thaliana accessions grown either individually or in bulk to determine how growth configuration and genotype shape the metabolism of sugars and organic acids during cold exposure. Using non-aqueous fractionation, we quantified plastidial, cytosolic, and vacuolar sugar pools alongside whole-cell carbohydrates, organic acids, enzyme activities, photosynthetic parameters, and stress markers. A neural-network classifier revealed that subcellular sugar distribution together with sugar amounts and organic acids provided the strongest discriminatory power among accessions, surpassing photosynthetic traits and enzyme activities. Our findings demonstrate that natural variation in cold acclimation is strongly determined by genotype-specific subcellular metabolite architectures, and that the cultivation strategy modulates these intracellular signatures. We conclude that subcellular compartmentation of metabolites represents a cellular control layer for natural variation of cold acclimation and resilience in Arabidopsis thaliana.

plant biology↗

bioRxiv2026

Ex vivo glioblastoma migration phenotypes define clinical recurrence and tumor heterogeneity

Glioblastoma's pronounced migratory capacity underlies its diffuse invasion, presenting a formidable barrier to successful treatment. Ex vivo characterization of glioblastoma cells isolated from freshly resected clinical samples under physiologically relevant conditions revealed two distinct migratory phenotypes, Fast Migrating (FM) and Slow Migrating (SM). These phenotypes reflect distinct mechanosensitivity profiles and are associated with pharmacological responses that support the motor clutch model of cell migration. Analysis of genes associated with these phenotypes revealed a transcriptomic signature that closely associated with in vitro cell migration, histological invasion in patient specimens, and clinical survival. Single-nucleus RNA sequencing revealed that FM and SM cells coexist within a single glioblastoma, with FM cells enriched at the periphery and SM cells localized to the tumor core. Collectively, our study demonstrates the utility of ex vivo glioblastoma characterization, allowing decoding of tumor heterogeneity and clinical prognostication as well as providing a framework for deconvoluting the complex cancer phenotype.

cancer biology↗