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Results for “systems biology”

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

Predictability failure in glucose-insulin system for ICU patients

Modern medicine implicitly assumes that physiological responses to intervention are predictably determined by administered treatments. However, physiological systems containing intrinsic delays between the detection of a stimulus and the biological response may violate this assumption. We investigate the human glucose-insulin system as described by the Ultradian model and mathematically demonstrate that clinically relevant forcing protocols-such as pulsatile insulin delivery and step-wise glucose infusion, both commonly used in intensive care units (ICUs)-can induce sustained temporal chaos that may hamper accurate prediction of the physiological response. If not accounted for, these chaotic dynamics could create difficulties in achieving optimal dosing and timing when administering glucose and insulin in clinical or home care settings. This phenomenon, termed delay-induced uncertainty (DIU), arises from the interaction between physiological delay, intrinsic shear near a limit cycle, and external forcing. Using the Ultradian glucose-insulin model, we compute top Lyapunov exponents to quantify predictability. Across a range of pulsatile and step-wise forcing regimes, including stochastic amplitudes drawn from Markov processes, we observe positive Lyapunov exponents, indicating sustained chaos. Our results suggest that delayed endocrine regulation may fundamentally limit the predictive value of the models used to develop glycemic management strategies, with implications for clinical protocols in the ICU.

systems biology↗

bioRxiv2026

Injury size regulates glucose allocation locally and systemically during vertebrate tissue regeneration

Tissue regeneration requires careful allocation of metabolic resources, yet how organisms adjust this allocation in response to varying amounts of tissue loss remains poorly understood. Here, we show that the regenerative metabolic response is not fixed: the size of an injury regulates how glucose is allocated at both local and organism-wide levels. We first demonstrate that tail regeneration requires glucose metabolism in the axolotl (Ambystoma mexicanum), a salamander capable of regenerating centimetre-scale tissues. We then mapped glucose uptake in axolotls regenerating from small or large tail injuries using positron emission tomography/magnetic resonance imaging (PET/MRI) and the radiolabelled glucose analogue [18F]FDG. Glucose uptake was elevated in regenerating tails compared to uninjured tails. During early regeneration, larger injuries induced higher glucose uptake than smaller injuries, correlating with faster regenerative outgrowth. Larger injuries also increased glucose uptake in distant organs, indicating a systemic metabolic response. Together, our findings suggest that metabolic responses tuned to injury size underlie faithful tissue regeneration and establish PET/MRI as a powerful approach for studying whole-body metabolic dynamics in large regenerating vertebrates.

developmental biology↗

bioRxiv2026

A patient-centric therapeutic paradigm uncouples prostate cancer suppression from systemic metabolic collapse

The clinical benefits of cancer therapies are often compromised by the tolerable adverse effects that impair systemic organismal health and may evolve into latent life threats. Here, we identified profound abiraterone-induced but androgen-independent metabolic perturbations in prostate cancer patients and developed Lifehug-9892 to balance tumor therapy with systemic metabolic homeostasis. By integrating population cohorts with high-resolution metabolomics, we demonstrate that abiraterone induces profound systemic lipidomic dysregulation, characterized by the massive, pathological accumulation of desmosterol. Abiraterone inhibits but stabilizes DHCR24, leading to a metabolic trap in patients showing elevated levels of both desmosterol and cholesterol. Desmosterol accumulation is highly lipotoxic, potently triggering endothelial cell senescence and necrosis, macrophage foam cell formation, murine atherosclerosis, and hepatic senescence. To mechanistically uncouple and therapeutically rescue this systemic metabolic collapse, Lifehug-9892 was rationally designed to selectively retain on-target CYP17A1 inhibition while completely sparing DHCR24 function. Lifehug-9892 maintains potent tumor-suppressive activity while fully preserving the desmosterol-cholesterol metabolic axis and preventing systemic cardiovascular and hepatic damage. Our study uncovers a critical mechanistic link between drug-induced metabolic dysregulation and organismal health in cancer patients, providing a biochemical framework for developing patient-centric targeted therapies that preserve host homeostasis.

cancer biology↗

bioRxiv2026

A Metabolic Labeling Strategy for Tracking Protein Synthesis in Complex Biological Systems

Protein synthesis supports most biological processes. In the brain in particular, protein synthesis plays a critical role in physiological and pathological states. Here, we describe Tellurophene-Alkyne Cycloaddition-mediated Amino acid Tagging (TeACAT), a versatile strategy for fast, facile, and flexible tagging of newly synthesized proteins in mice. TeACAT is based on metabolic incorporation of the non-canonical amino acid TePhe into proteins by the endogenous protein synthesis machinery. Due to their high similarity, TePhe can efficiently replace canonical Phe without dietary or genetic manipulation. The subsequent bio-orthogonal reaction of TePhe with either fluorescent dyes or affinity handles enables both visualization and affinity enrichment of proteins synthesized during TePhe exposure. TeACAT is compatible with immunofluorescence for cell-type specific visualization of protein synthesis with subcellular resolution and can be used in conjunction with routine proteomics to identify and quantify newly synthesized proteins. Robust incorporation into the mouse proteome was observed on the scale of hours to days, allowing the interrogation of various biological processes. In summary, TeACAT enables the visualization and quantification of protein synthesis with minimal perturbation for biological discoveries.

molecular biology↗

bioRxiv2026

The trade-off between parsimony and model complexity for understanding biomedical mechanisms from mathematical models

Mechanistic mathematical models have been used extensively to provide a deeper understanding of biological mechanisms, including unveiling the regulation of tumour growth and its response to various treatments. However, given the breadth of biological regulatory mechanisms, these models are frequently large and thus prone to potential issues with parameter identifiability. Statistical metrics like the Akaike and Bayesian information criteria can help identify a parsimonious model by balancing goodness of fit against model complexity. Yet simple models may fail to provide sufficient biological insight if they do not adequately capture known physiological processes or mechanisms. A modeller must therefore balance hypothesis generation and biological learning with model tractability. Here, we illustrate this balance using models of ovarian cancer growth and treatment response to cisplatin and immune checkpoint blockade in homologous recombination (HR)-deficient and HR-proficient immunocompetent mouse models. We develop a hierarchy of mathematical models of increasing complexity to describe tumour growth, treatment response, and immune dynamics. Our results highlight the limits of relying purely on statistical metrics for model selection, particularly when the goal is to obtain biological insight and underscore the importance of balancing model complexity to avoid overfitting and parameter unidentifiability.

systems biology↗

bioRxiv2026

Breeding cassava for intercropping with cowpea: monoculture selection captures most intercrop selection gain, but targeted testing remains necessary

Intercropping dominates smallholder cassava production in sub-Saharan Africa, yet cassava breeding programs evaluate genotypes exclusively under monoculture. Despite consistently reported system-level yield advantages, cassava yield is reduced by 17 to 51% under intercropping, indicating a need to reduce this competitive disadvantage through breeding. However, the quantitative-genetic foundations of intercrop breeding remain uncharacterized for tropical root crop systems. We hypothesized that monoculture selection would capture most, but not all, genetic merit for intercropping and that a limited tester set would be sufficient if general mixing ability predominated. We evaluated 120 cassava clones previously selected under monoculture in IITA advanced yield trials, testing them under monoculture and in intercrop with two contrasting cowpea varieties across two years at Ibadan, Nigeria. Spatial mixed models quantified genetic variation, genotype by cropping system interaction, cross system genetic relationships, realized selection gain, mixing ability, tester effects, and land equivalent ratio. Intercropping reduced cassava fresh root yield by 19%, but total land equivalent ratios exceeded 1.0 for all clones, confirming a system-level land use advantage. Cassava performance under intercropping was heritable, with estimates of 0.50 to 0.75, and genotype by cropping system interaction was not significant. Genetic correlations between monoculture and intercrop performance were high and approached unity (rg = 0.92 to 0.99), and selection efficiency was 26 to 44% at 10% intensity, confirming that high genetic correlation does not guarantee effective indirect selection. Monoculture selection captured approximately two-thirds of direct intercrop gain. General mixing ability dominated, specific mixing ability was negligible, and producer effects explained 20 to 47% of intercrop variance. The two architecturally and phenologically contrasting cowpea varieties had limited influence on cassava rankings. Here, we show for the first time that cassava breeding for intercropping can retain monoculture selection during early stages while adding two representative cowpea testers at the advanced trial stage. This staged strategy aligns cassava breeding with diversified smallholder systems without creating a separate pipeline.

plant biology↗

bioRxiv2026

Data coverage and model formulation reshape quantitative interpretations of bacterial transcriptional regulation

Thermodynamic models quantitatively describe interactions between transcription machinery and bacterial promoters. Contrary to conventional understanding, model analysis by Parisutham et al. (2025) attributes transcriptional inhibition by repressors to overstabilization of the RNA polymerase-promoter complex rather than prevention of its formation. Moreover, it suggests an inverse scaling relationship between basal promoter strength and transcriptional fold change, applicable to both repressor- and activator-mediated regulation. To reevaluate findings from this study, we systematically analyze empirical data and compare its framework with conventional thermodynamic models. In contrast to the inverse scaling relationship, data across multiple sources exhibit a peaked tradeoff between basal promoter strength and fold change, underscoring the importance of broad data coverage in revealing the full pattern required for reliable model inference. Furthermore, we identify the model assumption responsible for the apparent inverse scaling and misinterpretation of regulatory mechanisms. Relaxing this assumption enables the model to capture the peaked tradeoff and yield inferences consistent with established mechanisms of transcriptional repression and activation. We further derive a mathematical solution that connects basal expression to fold change for both repressor- and activator-regulated promoters. Our results underscore the importance of broad data coverage to avoid a blind-men-and-elephant interpretation and establish basal promoter strength as a key design parameter governing transcriptional regulation.

systems biology↗

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

Multiscale modelling of drug-host-pathogen interaction: quantifying drug and immune contributions to treatment response

Background and Objective: Predicting treatment outcomes in infectious diseases requires accounting for the interplay between drug effects, pathogen dynamics, and host immunity. Integrating pharmacological and immunological approaches into a single simulation environment remains a fundamental challenge in both theory and practice. We aimed to develop and validate a multiscale in silico framework coupling these processes, and to quantify their respective contributions to bacterial clearance. Methods: We present the Drug-Host-Pathogen Interaction (DHPI) framework, combining three independent mechanistic components: a physiologically based pharmacokinetic model of drug disposition, a pharmacokinetic-pharmacodynamic model of drug-induced bacterial killing, and a stochastic agent-based model of the immune response. Continuous concentration profiles are time-averaged onto the agent-based time grid, assigned to bacterial phenotypic states, and converted into per-agent killing probabilities, so that drug-mediated and immune-mediated death events are recorded separately at each step. The framework was applied to simulate symptomatic pulmonary tuberculosis. Phenotype-specific drug-efficacy parameters were inferred using Approximate Bayesian Computation from historical clinical data on eight weeks of 600 mg rifampicin monotherapy, and validated against independent early bactericidal activity data over a disjoint time window. Results: The calibrated framework reproduced the observed decline in bacterial load, and matched reported early bactericidal activity over the first week. In a virtual cohort of symptomatic patients, drug-mediated killing accounted for 81-88% and immune-mediated killing for 12-19% of total bacterial elimination over the 60-day treatment course, while the dormant, granuloma-contained fraction rose from 0.20-0.29 in the first week to 0.85-0.89 at treatment completion. Over a follow-up of up to 50 years, patients reaching clinical cure had accumulated more memory lymphocytes during treatment than those progressing to clinical failure or death; moreover, the final outcome depended on the immune changes occurring during therapy rather than on the initial disease stage. Conclusions: The results show that the DHPI framework can reproduce treatment dynamics observed in patients and enable the analysis of how therapy reshapes host immune responses and subsequent disease trajectories. By explicitly representing drug-host-pathogen interactions, it provides a mechanistic basis for in silico treatment simulations and for the study of long-term immune consequences of antimicrobial therapy.

systems biology↗

bioRxiv2026

GDNF enemas improve epithelial and immune defects in both aganglionic and ganglionic colon of Hirschsprung mice

Hirschsprung disease (HSCR) is a severe birth defect where ganglia of the enteric nervous system (ENS) are missing from distal bowel. The aganglionic segment is also characterized by increased epithelial permeability and pro-inflammatory immune activation. These problems may sequentially lead to translocation of gut microbes into the colon wall and systemic circulation, resulting in enterocolitis and sepsis. Current HSCR treatment via surgical resection of the aganglionic segment is lifesaving but not curative, often leaving patients with persistent gastrointestinal complications including recurrent risk of enterocolitis. As alternative, we are developing a regenerative medicine strategy based on in situ stimulation of tissue-resident ENS progenitors via rectal administration of the neurotrophic factor GDNF. Here, we report that GDNF-based therapy has pleiotropic gastrointestinal effects in a mouse model of short-segment HSCR, beyond its role in ENS regeneration. Interestingly, we found that these protective effects are not restricted to the aganglionic distal colon, also positively impacting the ENS-containing proximal colon. GDNF treatment reduces bacterial translocation both locally and in peripheral organs, and this is associated with recovery of the key epithelial junction proteins CLDN3, ZO1 and DSG2. Furthermore, multiparameter flow cytometry-based analysis of 55 lymphoid and 17 myeloid cell subtypes revealed that GDNF treatment has global anti-inflammatory effects, preferentially affecting innate over adaptive immunity. Overall, these findings highlight a critical role for GDNF treatment in reestablishing proper epithelial and immune cell homeostasis, offering promising therapeutic avenues not only for HSCR but also potentially for other intestinal disorders with overlapping pathophysiology.

developmental biology↗

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

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

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

Nuclear Myosin VI stabilises Ku-associated DNA ends during non-homologous end joining

DNA double-strand breaks (DSBs) require rapid signalling and physical stabilisation of broken DNA ends to preserve genome integrity. Here, we identify myosin VI (MVI) as an ATM-regulated component of the DSB response. DNA damage induces rapid nuclear accumulation and nanoscale reorganisation of MVI across multiple cell models, in an ATM-dependent manner. Pharmacological or genetic perturbation of MVI attenuates {gamma}H2AX signalling and disrupts Ku80 organisation, while DNA damage persists. This leads to increased sensitivity to cisplatin and bleomycin. Super-resolution imaging reveals spatial association of MVI with Ku80-containing repair structures, implicating MVI in non-homologous end joining (NHEJ). In a minimal reconstituted system, MVI and actin enhance the proximity of Ku70/80-bound DNA ends. Together, our findings identify MVI as a regulator of DSB repair that links ATM signalling to Ku-associated DNA-end stabilisation and suggest that targeting MVI may sensitise tumour cells to genotoxic therapy.

cancer biology↗

bioRxiv2026

Scalable proxiloids enable human-relevant assessment of kidney proximal tubule toxicity

Drug-induced injury to the human proximal tubule (PT) is a leading cause of acute kidney injury and drug attrition, yet remains difficult to predict preclinically. PT toxicity arises from the coupling of transporter-mediated xenobiotic accumulation and high oxidative metabolic demand. Current models lack key aspects of PT physiology or are difficult to scale for toxicity testing. New Approach Methodologies (NAMs) address this challenge through human-relevant in vitro systems. Here we introduce proxiloids, a scalable suspension-based human induced pluripotent stem cell differentiation strategy. Within 14 days, proxiloids form lumenized, polarized tubular organoids enriched for PT identity, with functional transport and oxidative metabolic competence. Proxiloids are compatible with genetically encoded reporters and standard multiwell assays, enabling detection of defined stress responses. They recapitulate aminoglycoside nephrotoxicity with greater sensitivity than matched two-dimensional cultures and detect adefovir-induced mitochondrial toxicity not predicted in rodents. Together, proxiloids provide a scalable, human-relevant NAM for PT nephrotoxicity assessment.

cell biology↗

bioRxiv2026

A Microneurosurgical Survival Platform for Elucidating Mechanisms of Brain Tumor Recurrence and Metastasis

Brain tumor recurrence remains the leading cause of mortality in neuro-oncology, and there is a lack of preclinical models replicating the clinical cycle of surgical resection and relapse. To bridge this gap, we developed a novel microneurosurgical survival platform in mice using the NICO Myriad system. We orthotopically implanted pediatric medulloblastoma cells into the mouse cerebral cortex or cerebellum, followed by longitudinal microneurosurgical resection. Bioluminescence imaging and gross fluorescence verified successful resection, local and distal recurrence and metastasis. Comparative bulk RNA sequencing revealed extensive stage-specific transcriptomic divergence alongside conserved core gene sets (2,702 genes in the cerebral cortex and 3,240 genes in the cerebellum) across primary, locally recurrent, and distally recurrent stages. Pathway analysis shows activation of cellular growth, second messenger signaling, and cellular stress adaptation pathways. Targeted qPCR validation demonstrated that post-surgical relapse is driven by a distinct molecular program: recurrent tumors downregulate primary developmental drivers (PTCH1, MYCBP2), canonical suppressors (FOS, PTEN), and chromatin regulators (HDAC2), while selectively upregulating post-transcriptional machinery (RBM8A), endosomal trafficking regulators (RAB5C), acetyltransferases (NAA15), and the m6A RNA demethylase ALKBH5. These findings reveal that medulloblastoma shifts from a primary oncogenic state toward post-transcriptional and transcriptomic survival mechanisms following surgery. Identifying persistent candidates within this conserved core framework provides a roadmap for next-generation precision immunotherapies.

cancer biology↗

bioRxiv2026

Structural basis for catalytic and inhibitory divergence between archaeal and bacterial ammonia monooxygenases

Ammonia oxidation initiates nitrification and is closely linked to microbial N2O production. Ammonia monooxygenase (AMO) catalyzes the first and rate-limiting step of nitrification and is widespread across evolutionarily distinct ammonia-oxidizing archaea (AOA) and bacteria (AOB). The ocean is the largest biome for AOA and AOB, which have distinct ecological niches and markedly different sensitivities to nitrification inhibitors. However, the lack of archaeal AMO structures and inhibitor-bound AMO complexes has hindered mechanistic understanding of the architectural, catalytic, and inhibitory divergence between these two enzyme systems. Here, we report high-resolution cryo-electron microscopy (cryo-EM) structures of marine archaeal AMO captured in active and inactivated states within its native membrane environment, together with inhibitor-bound structures of estuarine bacterial AMO. Archaeal AMO forms an unexpected cup-shaped homotrimer composed of eight subunits per protomer and exhibits substantial architectural divergence from bacterial AMO. Integrated structural, biochemical, kinetic, and computational analyses reveal distinct periplasmic architectures, copper-center organization, and hydrophobic channels between archaeal and bacterial AMOs for ammonium acquisition, catalysis and inhibitor response. These findings provide a structural and mechanistic framework for understanding how archaeal and bacterial AMOs have diverged to distinct ammonia-oxidizing strategies and inhibitor susceptibilities across environmentally important ammonia oxidizers.

molecular biology↗

bioRxiv2026

Half-match recombination drives bridge RNA-guided excision and off-target insertion

IS110-family bridge recombinases are a recently identified class of compact, RNA-guided editors in which a bridge RNA (bRNA) directs the recombination of a donor DNA into a target site. In the current model, the bRNA engages fully complementary donor and target sequences within a single synaptic complex to drive double-stranded recombination, implying that the transposon is cut from its donor site rather than copied, yet neither the strandedness of the excised intermediate nor the requirement for full complementarity has been tested directly. Here we reconstituted IS621 recombination in a cell-free transcription-translation system, building representative arrangements of the excision and insertion reactions and characterizing the outcomes. We find that IS621 predominantly excises a single strand, releasing a single-stranded circle and leaving the donor site intact, consistent with copy-and-paste transposition. By introducing mismatches into the bRNA target sequences, we further find that excision proceeds independently of target-site complementarity, relying strictly on donor-arm recognition; we term this "half-match" recombination, because a substrate matching only half of the bRNA is sufficient. We also find half-match activity during insertion, both in vitro and in a published genome-editing experiment, where it accounts for approximately half of non-target insertion reads. Half-match recombination provides both a mechanistic explanation for off-target insertion and a framework for the rational design of high-fidelity bridge recombinases.

molecular biology↗