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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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

Engineering nanocondensate formation through sequence composition and patterning

Many biological proteins can assemble into dynamic, non-stoichiometric structures known as biomolecular condensates. Although typically observed at micrometer scales in vitro, recent evidence shows that these condensates often appear as nanoscale assemblies both in vitro and in cells. Moreover, biochemical reactions can be more efficiently promoted in nanoscale condensates than in micron-sized droplets, due to mass-transfer limitations and interfacial effects. Therefore, in analogy with colloids, the function of condensate materials can be engineered by tuning their size distribution. However, controlling the size of condensates remains challenging, as the molecular mechanisms that prevent small condensates from coarsening into larger ones are still poorly understood. Here, we developed and applied a computational pipeline that combines high-throughput molecular simulations, machine learning, and mixed-integer linear programming to design phase-separating peptides that form metastable nanocondensates across a broad range of experimental conditions. In addition to experimentally validating these peptides, we elucidate the underlying molecular mechanisms and derive initial design rules. In particular, we show that scaffold net charge combined with sequence blockiness can lead to high phase separation propensity while simultaneously yielding low interfacial tension, thereby slowing ripening. Moreover, these combined properties induce an electrostatics-driven alignment of molecules at the interface, which generates an additional size-dependent coalescence barrier. We further show that these features are shared by biological proteins, providing a possible mechanistic basis for the widespread occurrence of nanocondensates in biological systems. Altogether, our findings shed light on the molecular mechanisms behind nanocondensate formation, and provide a platform to design nanocondensates for several potential applications in bioengineering and biotechnology. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/706365v2_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@17c379aorg.highwire.dtl.DTLVardef@26686dorg.highwire.dtl.DTLVardef@19206a7org.highwire.dtl.DTLVardef@1f2da71_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

Unravelling the memory of the extracellular matrix using MASH-derived decellularized scaffolds

The use of decellularized diseased livers in regenerative medicine is a promising approach for eliminating organ shortages. Bioengineering studies have shown that ECM can impact cell physiology, inducing cell activation, function, and ECM deposition, which suggests that the ECM has a "memory" that is involved in the outcome after recellularization. However, the effect of diseased ECM memory on new cells in vitro and in vivo has not been thoroughly investigated. Since it has been increasingly recognized that liver ECM changes due to different factors, it is comprehensively that diseased ECM obtained from discarded organs will ensure a distinct environment and impact cell survival and physiology. Thus, we aimed at investigating the impact of the memory of diseased ECM obtained from metabolic dysfunction-associated steatohepatitis (MASH)-derived organs on steatohepatitis establishment. To address this aim, we explored decellularized ECM obtained from rats and humans with MASH in different contexts. First, MASH ECM was characterized and then submitted to transplantation to investigate whether a MASH-derived ECM could be used as a scaffold for transplantation and to promote steatohepatitis features in control animals. Histological analysis revealed that the MASH-ECM was completely recellularized after transplantation in both control and MASH recipient rats. However, steatosis and fibrosis were observed in MASH ECM after transplantation in both groups. Molecular analysis showed that MASH ECM stimulates de novo lipogenesis and fibrosis 30 days after transplantation. Untargeted metabolomic analysis revealed that cells grown on MASH ECM had a similar metabolic profile, even when transplanted into healthy or MASH recipient rats. In addition, we observed that MASH ECM promoted impaired lipid oxidation and mitochondrial dysfunction when transplanted into healthy recipients. Altered lipid turnover and inflammatory signaling were observed in MASH ECM transplanted in MASH recipients. In vitro analysis revealed that MASH ECM induced lipid accumulation in HepG2 cells after 10 days of culture. Calcium signalling experiments obtained from HepG2 cells cultured in MASH ECM showed a lower response to ATP, a reduced calcium signalling amplitude, and a distinct response profile than that observed in healthy ECM. On the other hand, a diseased human-derived ECM could still provide an environment that allows cell development. Taken together, our data showed that MASH ECM impacts cell metabolism, promoting steatohepatitis maintenance. In conclusion, our data confirm that diseased ECM memory can impact cell physiology contributing to disease progression.

physiology↗

bioRxiv2026

A comprehensive reference database to support untargeted metabolomics in Pseuudomonas putida

Pseudomonas putida strain KT2440 is a crucial model organism for synthetic biology and bioengineering applications, yet there currently exists no comprehensive metabolomics database comparable to those available for other model organisms. This gap hinders the use of untargeted metabolomics for exploratory analyses in this system. We developed the P. putida metabolome reference database (PPMDB v1) to address this limitation by consolidating metabolite information from multiple sources and expanding coverage through computational predictions. The database was constructed by curating metabolites from BioCyc, BiGG, and other literature sources, then computationally expanding this collection using BioTransformer environmental transformation predictions to generate additional predicted metabolites. We enhanced the databases utility for molecular annotation in metabolomics studies by incorporating analytical properties including collision cross-sections, tandem mass spectra, and gas-phase infrared spectra. These analytical properties were gathered from existing measurement data or predicted using computational tools. We further augmented the database through inclusion of reaction information and pathway annotations, facilitating biological interpretation of metabolomics data. This publicly available resource fills a critical gap in P. putida research infrastructure, supporting metabolite annotation and biological interpretation in untargeted metabolomics studies and enabling in-depth exploratory analyses of this important synthetic biology platform at the molecular level. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/713193v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@c8828forg.highwire.dtl.DTLVardef@1f3a5c5org.highwire.dtl.DTLVardef@1084535org.highwire.dtl.DTLVardef@1f7ca4a_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

EMS Mutation and SNP Detection in Intracellular Wolbachia Genomes

Endosymbiotic bacteria such as Wolbachia pose significant challenges to genetic and molecular investigation due to their obligate intracellular lifestyle and complex growth requirements.Current understanding of their protein biology relies heavily on functional assignments inferred by homology, which may not reflect the specific roles endosymbiont proteins play within the host. This work addresses the need for robust genetic perturbation by demonstrating the successful application and detection of chemical mutagenesis in the genome of the wMel strain of Wolbachia grown within a stably infected Drosophila melanogaster JW18 cell line. To accurately detect EMS-induced mutations in a large, unsorted cell culture population, in which mutations remain at very low allele frequency, we implemented an ultra-low error rate sequencing strategy, circle sequencing. This technique enables confident detection of EMS-induced single nucleotide polymorphisms (SNPs) that would be swamped by the inherent error rates of standard next-generation sequencing. Circle sequencing library preparations successfully revealed a clear EMS mutation signal in treated cells, characterized by a significant enrichment of canonical C/G>T/A transitions. Furthermore we present a model explaining observed EMS mutation rates across the genome for different sequence contexts. These findings show that EMS-treatment can successfully leave detectable mutation signals in intracellular genomes, and offer promise for the future development of protocols to make targeted edits in Wolbachia genomes. ImportanceAs the use of intracellular symbionts for bioengineering projects grows, so does the need for foundational protocols for the genetic manipulation of intracellular genomes. Ethyl methanesulfonate (EMS), a chemical mutagen, has been a research tool for initial genomic analysis of gene function in plant and animal systems for decades and represents an established way of generating mutations for future functional testing.

genomics↗

bioRxiv2026

Mechanical confinement drives monocyte-to-macrophage differentiation

Cells in vivo experience mechanically diverse microenvironments in which physical confinement is a pervasive but poorly understood regulator of their behavior and fate. Whether and how mechanical confinement governs immune cell differentiation remains unknown. Here, we reveal that a mechanical cue -- long-term confinement is sufficient to drive monocyte-to-macrophage differentiation through a mechanoepigenetic pathway. In vivo, differentiating monocytes exhibited flattened nuclei in the liver capsule, indicative of confinement by surrounding stromal and parenchymal structures. Using a custom cell confiner to recapitulate this confined niche, we found that confinement induces macrophage-like protrusive architectures, enhances motility, and upregulates macrophage-associated genes in RAW264.7 and THP-1 monocyte-lineage cells. Notably, extending this paradigm to primary murine bone-marrow, human umbilical-cord, and tissue-derived hepatic-associated monocytes yielded similar outcomes, thus enhancing phagocytic capacity, directly demonstrating that mechanical confinement can program monocytes into macrophages. Mechanistically, we found that confinement activates KDM6B, leading to H3K27me3 demethylation, which derepresses macrophage-specific transcriptional programs. Pharmacological inhibition of KDM6B with GSK-J4 restored H3K27me3 and blocked macrophage differentiation both in vitro and in vivo. These findings define a KDM6B-H3K27me3 axis that links nuclear mechanics to transcriptional reprogramming, positioning mechanical confinement as a "super-enhancer-like" cue for engineer macrophage function in therapeutic and bioengineering contexts.

cell biology↗

bioRxiv2026

The anaerobic fungus Caecomyces churrovis produces H2 via a non-bifurcating NADH-dependent enzyme complex

Hydrogenosomes are mitochondria-derived organelles that produce ATP and H2 to support energy metabolism in anaerobic eukaryotes. H2 production allows reoxidation of reduced cofactors generated during fermentative metabolism; however, the metabolic mechanisms for H2 production in anaerobic eukaryotes remains incompletely understood. In particular, it remains unclear whether anaerobic fungi (AF) hydrogenosomes use a ferredoxin-dependent pathway or a distinct mechanism to regenerate NAD(P)+ and link electron transfer to H2 formation. Here, by combining genomic search, proteomic analysis, and enzymology, we reveal the molecular mechanism for H2 production in the AF strain Caecomyces churrovis. Our enzyme assays on the organelle fraction of C. churrovis revealed the activity of H2:NAD+ oxidoreductase but not pyruvate:ferredoxin oxidoreductase, which is usually linked to H2 formation. We identified genes encoding [FeFe] hydrogenase (Hyd) and NADH dehydrogenase subunits E and F (NuoE, NuoF) in C. churrovis, and confirmed their expression in the isolated hydrogenosomal fractions by proteomic analysis. Combining the individually purified enzymes, we found Hyd and NuoEF proteins formed H2 directly from NADH independently of ferredoxin, functioning as a non-bifurcating NADH-dependent enzyme rather than an electron-bifurcating enzyme. We identified homologs of hydrogenosomal NuoE, NuoF, and Hyd in many other AF, indicating this pathway is commonly shared among the AF. This work demonstrates the existence of a non-bifurcating NADH-dependent enzyme complex in eukaryotes. Moreover, this complex could potentially be exploited as a target for controlling AF H2 production and altering fungal metabolism. IMPORTANCEH2 production is a prominent feature of anaerobic energy metabolism, yet our understanding of eukaryotic mechanisms remains limited. Anaerobic fungi (AF) are key decomposers of lignocellulose and contribute to hydrogen flux in anaerobic environments. Although it has been more than 40 years since the H2 production from AF was first reported, the molecular mechanism for hydrogenosomal H2 production and redox balance remains unclear. We demonstrate that AF produce H2 from NADH utilizing a non-bifurcating NADH-dependent enzyme complex rather than an electron-bifurcating, ferredoxin-dependent variant. We show that this enzyme complex is conserved across multiple AF lineages and thus demonstrate the occurrence of a non-bifurcating NADH-dependent enzyme in eukaryotes. This discovery expands our understanding of eukaryotic hydrogenosomal metabolism, reveals a previously unknown strategy for redox balancing, and highlights potential targets for manipulating H2 production. These insights have broad implications for microbial energy metabolism, anaerobic ecosystems, and bioengineering of H2-producing systems.

microbiology↗

bioRxiv2026

DyME: An MD-based engine exploiting HTP mutagenesis for protein engineering and recognition mimicry

Protein recognition mimicry is of great interest in the field of molecular bioengineering and rational design, with mutagenesis frequently employed to analyze the effects of altering amino acids involved in molecular recognition. The conformational and energetic effects of such alterations can be investigated in detail with the help of molecular dynamics (MD) methodologies. While existing MD-based computational tools can be used to explore a particular set of mutations at a time, suitable for small-scale studies, high-throughput (HTP) exploration of protein recognition for engineering purposes would greatly benefit from an integrative platform that streamlines preparation, mutagenesis, simulation and post-processing of up to several thousand molecular systems, along with robust tools for comprehensive and straightforward comparative analysis. DyME (Dynamic Mutagenesis Engine) is a distributed platform that enables systematic investigations of protein recognition mimicry by combining HTP mutagenesis, solvated MD simulations and a Toolbox for comparative analysis (TCA), including interfacial water-site mapping. DyME uses 3D structural information of any protein-protein or protein-DNA complex as input. Its automated MD-based mutagenesis engine facilitates systematic investigation of how site-specific alterations affect recognition, enabling the organization of single, double and triple modifications into combinatorial libraries for comprehensive comparative analysis. In DyME, relevant MD trajectory-derived data is scavenged and stored into a central database, providing aggregation capabilities that ease multi-feature analysis across an extensive collection of simulations. An interactive web-GUI and specialized widgets simplify preparation and efficient molecular and numerical comparative exploration. DyMEs capabilities are evaluated using available experimental data. Its source code is available at https://github.com/pisabarro-group/DYME

bioinformatics↗

bioRxiv2026

Domain-swapped LuxR-type quorum sensing receptors reveal divergent ligand-response mechanisms among homologs

Many common bacteria use quorum sensing to regulate cell density-dependent phenotypes, including luminescence, biofilm formation, virulence, and symbiosis. The LuxI/R system is the best-characterized quorum sensing pathway in Gram-negative bacteria and consists of a LuxI-type synthase that produces an N-acyl L-homoserine lactone (AHL) autoinducer and a LuxR-type transcription factor that is regulated by AHL binding. Binding of native AHL signal promotes DNA binding and transcriptional regulation in some LuxR homologs (associative-type), while other homologs regulate transcription in the absence of ligand and are inactivated by native signal binding (dissociative-type). To better characterize what features determine ligand-response type, we generated structural mutants of two associative receptors (LasR of Pseudomonas aeruginosa and MrtR of Mesorhizobium tianshanense) and two dissociative receptors (EsaR of Pantoea stewartii and ExpR2 of Pectobacterium versatile). Swapping domains between these receptors revealed that the ligand-binding domain primarily determines associative vs. dissociative activity in response to native AHL agonists. Further, non-native AHL-derived antagonists maintained their activity profiles in receptors with interchanged DNA-binding domains. We also found that the extended linker between domains observed in the dissociative receptors does not determine mechanism of ligand response, and that inter-domain interactions may play an important role in activation for some receptors but not others. Notably, deletion of just one residue from the dissociative receptor EsaR produced a mutant with associative activity, the first time such mechanism switching has been reported for a LuxR-type receptor. These findings illuminate features essential for ligand response and highlight the mechanistic diversity of the LuxR family. IMPORTANCELuxI/R quorum sensing regulates various cell density-dependent phenotypes in Gram-negative bacteria. Prior research has developed small molecule modulators of LuxR-type receptors, with potential applications in anti-virulence, anti-biofouling, and bioengineering. Competitive antagonists have been reported for receptors active in the presence of native ligand but not for receptors active in its absence. A lack of knowledge about the molecular mechanisms of receptor response to ligand limits both our fundamental understanding of the LuxI/R quorum sensing process and the rational design of chemical modulators with superior activity profiles. We used a structural mutagenesis strategy with four LuxR-type receptors that operate via two distinct mechanisms to begin to dissect the structural features that drive differences in ligand response between receptors. These insights could aid in efforts to characterize novel LuxR homologs, understand potential interspecies communication via quorum sensing, and develop improved chemical probes to alter LuxR-type receptor activity.

microbiology↗

bioRxiv2026

Sex-differentiated hormonal microenvironments recapitulate in vivo liver metabolism in human iPSC-derived organoids

Bioengineers strive to recreate in vivo microenvironments in vitro to reduce our use of animal models and provide insights into human biology. While liver models show promise, sex differences in liver biology remain largely neglected in preclinical studies. Despite the 2014 EU mandate for the inclusion of women in clinical trials, decoupling of research data by sex is historically rare, with only 11% of papers disaggregating data by sex. This gap contributes to women being more susceptible to drug-induced liver injury (DILI) and being underserved in drug development, as well as to costly drug attrition levels. Here we present a novel approach to modelling sex differences in vitro. Human induced pluripotent stem cells (iPSCs) from both male (XY) and female (XX) donors, were differentiated into hepatocyte liver spheroids and exposed to in vivo-mimicking levels of testosterone, progesterone, and oestrogen in high-throughput microwell format. We successfully recapitulated sex-specific metabolic profiles and demonstrated significant differences in CYP1A2 and CYP3A4 drug metabolism and gene expression patterns consistent with reported in vivo observations, without compromising cell viability. These findings validate the utility of sex-differentiated microenvironments in early-stage research, offering a pathway to refine animal and clinical trials and improve therapeutic outcomes for all sexes.

cell biology↗

bioRxiv2026

Coarse-graining metabolic networks via feature learning reveals cross-species growth laws

Bacterial growth and the underlying metabolic networks are highly dissimilar across species, posing a fundamental challenge for bioengineering tasks involving diverse species. For a given species across nutrient environments, growth is regulated via proteome allocation, which gives rise to linear relationships between growth and the sizes of coarse-grained proteome sectors. However, whether and how coarse-grained growth predictors generalize across species remain unclear. Here, using genome-scale metabolic models, we discover a simple cross-species trend in which the monoculture growth of a species is proportional to the number of nutrients it utilizes, indicating that the latter is a regulatory feature that is conserved across species. By coarse-graining metabolic networks using feature learning, we identify novel proteome sectors whose sizes exhibit cross-species correlations with growth in wide-ranging experiments, suggesting that these sectors are also conserved regulatory features. We further show that the sectors enable a predictive encoding of proteome costs and growth benefits, thereby providing a potential explanation for how coarse-grained network features emerge to be simple determinants of growth across diverse metabolic networks.

systems biology↗

bioRxiv2026

Toward resolving gravitational effects on microbial growth with computer simulations

As the duration of space flights increases, so does the need to optimize off-planet microbial growth. Microbes can both be unintentionally brought into space and cause human disease or be intentionally harnessed for on-site bioengineering functions. However, optimizing microbial growth is challenging due to an insufficient understanding of how microbial communities are affected by the extraterrestrial environment. To address this gap, we have modified a previously developed model for cell growth in microgravity. By improving the functional form used for cell growth as well as the code usability, we enable further research into how microbial communities are influenced by gravity. Applying this model to isolate individual effects of gravity on cell growth indicates that a lack of gravity-driven flow decreases cell growth in microgravity, while the absence of sedimentation increases cell growth in microgravity. These opposite effects likely contribute to the system-dependent effects of microgravity observed experimentally.

biophysics↗

bioRxiv2026

MetworkPy A Python Package for Graph- and Information-theoretic Investigation of Metabolic Networks

SummaryWe present MetworkPy, a python package for investigating in silico genome-scale models of metabolism (GSMM). By using novel graph- and information-theoretic methods to explore the feasible reaction flux space, MetworkPy quantifies network context and simulates metabolic relationships between sets of enzyme-encoding genes without imposing assumptions of optimal growth. To demonstrate utility, we used MetworkPy to identify metabolic features perturbed by the transcription factor ArgR, a known regulator of arginine biosynthesis in Mycobacterium tuberculosis, based on published transcriptome data generated from an argR mutant strain. MetworkPy successfully linked reaction flux shifts in ArgRs transcriptome-constrained GSMM to arginine biosynthesis, which cannot be easily ascertained by conventional constraint-based optimization modeling approaches. MetworkPy offers a flexible toolbox for metabolic contextualization of genes-of-interest in microbial, eukaryotic, and multi-organism systems with potential applications for medicine and bioengineering. Availability and implementationThe MetworkPy package can be retrieved from PyPi (https://pypi.org/project/metworkpy/) and GitHub (https://github.com/Ma-Lab-Seattle-Childrens-CGIDR/metworkpy). Code for analyses performed in this paper can be retrieved from GitHub (https://github.com/Ma-Lab-Seattle-Childrens-CGIDR/metworkpy_application_note) Supplementary InformationSupplementary data are available online at bioRxiv.

bioinformatics↗

bioRxiv2026

Purinergic signaling disrupts emergent patterns of multicellular coordination in basal Xenobots.

The ability of self-organizing systems to display emergent, adaptive capabilities is a fundamental feature of biological life. Understanding the mechanisms by which cells co-ordinate at the micro-scale to produce macro-scale structures and behaviors is a fundamental problem in developmental biology. Moreover, it is an important goal of biomedicine to identify triggers that re-wire the physiological patterns of information flow and control signals. Here, we use a recently developed, synthetic biology platform known as basal Xenobots to explore how patterns of information flow and multi-cellular integration are regulated by chemical signaling pathways. Basal Xenobots are modified, organoid-like systems constructed from embryos, and have previously been shown to display complex patterns of information flows. In this study, we recorded calcium signals before and after exposing basal Xenobots to extra-cellular adenosine triphosphate (eATP), and used statistics from multivariate information theory to explore the differences in global patterns of information flow across the cells in each state. We found that eATP resulted in a dramatic reconfiguration of global information processing dynamics, characterized by a global decrease in multi-cellular co-ordination, reduced information transfer and integration, and a decrease in the global entropy rate of the basal Xenobots. These results provide evidence that purinergic signaling may play a key role in the regulation of multi-cellular self-organization, with implications for a variety of clinical disorders thought to involve aberrant purinergic signaling. These results also suggest the possibility that bioengineers may be able to "tune" the degree of self-organizing capacity in living systems via pharmacological intervention.

systems biology↗

bioRxiv2026

FCRL5 is a fucose-sensitive IgG-Fc receptor with binding properties distinct from classical Fcγ receptors

Fc receptor-like protein 5 (FCRL5) is a low-affinity IgG receptor expressed on B cells, with emerging therapeutic relevance due to its expression on multiple myeloma cells, and a potential role in regulating B cell responses. Previous reports on the FCRL5-IgG interaction vary widely in reported affinities, binding differences across IgG subclasses, and molecular requirements for maximal binding. Furthermore, the impact of Fc-engineering strategies, as used in (therapeutic) monoclonal antibodies, remains poorly understood. Here, we provide a comprehensive biochemical analysis of the FCRL5-IgG interaction. We demonstrate that FCRL5 is a true IgG Fc-receptor, binding with very low affinity (60-80 {micro}M). FCRL5 binds IgG in a manner involving primarily the two N-terminal domains of FCRL5, and the third domain for maximal binding, but with distinct essential residues in the IgG Fc-tail. Surface plasmon resonance analysis of the binding of FCRL5 to the various IgG subclasses revealed a preference for IgG1 and IgG4. Interestingly, various Fc-engineered IgG variants commonly used for silencing or enhancing of Fc receptor binding do not impact FCRL5 binding. Screening the binding of a set of IgG antibodies carrying defined sets of Fc-mutations to FCRL5 revealed E293 as a key binding determinant and led to the discovery of E293R as a mutation that selectively abrogates FCRL5 binding while preserving binding to other classical Fc{gamma}Rs. Lastly, we show that FCRL5 has considerable preference for binding afucosylated IgG. Together, our results define the essential characteristics of the IgG-FCRL5 interaction and demonstrate the potential of both naturally occurring IgG variants as well as therapeutically explored bioengineered IgG formats to differentially engage FCRL5.

immunology↗

bioRxiv2026

Biocontainment of phages inhibits bacterial clearance in micro niches

Phage therapy offers a promising solution to the antimicrobial resistance crisis. However, a major concern preventing the adoption of phage therapy is the potential for unintended consequences of phage release; both in regard to preventing the spread of phage resistance, and the proliferation of a non-endemic virus into the microbial ecosystem. Conditional replication (biocontainment) of phages through bioengineering may address these concerns, but the impact on bactericidal efficacy is unknown. Here, we created a biocontained T7 phage (T7{Delta}capsid) lacking the major structural capsid gene, gp10AB, that can only replicate on Escherichia coli strains expressing gp10AB in trans, and assessed its bactericidal efficacy compared with wild-type T7. Congruent with model predictions, T7{Delta}capsid was only able to clear a well-mixed culture of E. coli at a multiplicity of infection (MOI) of 10 or higher, whereas wild-type T7 prohibited growth at an MOI of 0.1. The reduction in efficacy was more evident in a complex structured environment within a microfluidic device, where phage success depends on its ability to penetrate a microbial niche via propagation. In this environment, T7{Delta}capsid was unable to propagate into the bacterial population and unlike wild-type T7, had no impact on the populations growth. This study shows that whilst biocontainment of phages may improve the biosafety of phage therapy, it comes at the cost of its propagation efficacy and niche penetration in relevant environments.

microbiology↗

bioRxiv2026

Barcoded-Plasmid DNA library construction for recording cell lineage trees enabled by a Scalable and modular Biofoundry-based Automated Robotic Pipeline

High-quality plasmid DNA purification at high throughput remains a significant bottleneck in molecular biology and bioengineering. Current methods frequently fail to deliver sufficient yields of pure, transfection-grade DNA required for genetic engineering applications in mammalian cells. Here, we present a Biofoundry-based automated pipeline using the CyBio FeliX robotic liquid handling platform to rapidly purify plasmid DNA with minimal manual intervention. The protocol leverages Solid Phase Reversible Immobilisation (SPRI)-based magnetic bead technology to ensure consistency, scalability, and DNA purity suitable for downstream viral particle production and mammalian cell transfection. The pipeline supports flexible processing of between 8 and 96 samples per run, making it adaptable across a wide range of experimental scales. The protocol is openly available via Earlham Institute GitHub repository, enabling broad adoption across the bioscientific community and contributing to the growing toolkit of reproducible, scalable engineering biology workflows. In this work, we employed an integrated robotic pipeline to process 528 pooled DNA plasmids and built a Lentiviral DNA plasmid library for lineage tracing, validated the library by sequencing, and demonstrated efficacy in downstream mammalian cell transfection experiments.

synthetic biology↗

bioRxiv2026

A scalable mesh microelectrode array platform for longitudinal electrophysiology in neural spheroids

Electrophysiological interfacing remains difficult in three-dimensional in vitro models, when using planar microelectrode arrays or optical methods. This challenge limits experimental progress using such models, despite their promise of better physiological relevance than monolayer cell culture. Mesh MEAs which can integrate conformally on or even within tissue offer a possible solution but are not yet widely accessible. Here, we present a mesh MEA device, designed as a simple, manufacturable platform for spheroid electrophysiology. In neural spheroids, the device enabled longitudinal electrophysiological recordings and pharmacological modulation of spontaneous electrical activity. On native polyimide meshes, spheroids maintained their shape while cells enveloped the mesh, embedding electrodes to a depth of 100 {micro}m after 2 weeks. In contrast, laminin biofunctionalization of the mesh promoted outgrowth and migration of cells. This device and associated methods should be adaptable to organoids, ex vivo tissue, or bioengineered in vitro models.

neuroscience↗

bioRxiv2026

Continuous target-specific mutagenesis and rapid gene evolution by diversity-generating retroelements in Escherichia coli

Sequence-programmable directed evolution systems have great potential to accelerate bioengineering. Diversity-generating retroelements (DGRs) are natural hypermutation systems widely distributed in prokaryotes and bacteriophages with the capacity to introduce diverse mutations at template-specified sites of target genes. Here, we show that DGRs can be installed in E. coli and reprogrammed for the continuous, iterative mutagenesis of user-defined target genes. We show that the DGR template RNA can be reprogrammed for gene- and residue- specific mutagenesis, leaving untargeted, adjacent residues unchanged. Furthermore, we establish continuous DGR-enabled mutagenesis with F-plasmid-mediated horizontal gene transfer of target genes (HGT-DGR) into a new host for the progressive accumulation of target- specific mutations. Iterative HGT-DGR mutagenesis over seven cycles yielded an average mutation load of approximately 6% across adenine positions in the target segment, generating a diverse library of variants comprising 40% mutant sequences, with a median pairwise Hamming distance of 4 among mutant variants. HGT-DGR enables iterative diversification of either the same or different user-specified segments of the target gene, as demonstrated with the directed evolution of the M. mazei pyrrolysyl-tRNA synthetase for non-canonical amino acid incorporation. HGT-DGR provides a simple, low-cost, sequence-programmable system that enables iterative, position-specific and tunable in vivo mutagenesis of any target sequence for applications in biotechnology and medicine.

synthetic biology↗