Synthetic Biology

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.

The Modular Cloning (MoClo) and PhytoBrick standards have revolutionized plant synthetic biology by establishing a standardized, hierarchical assembly grammar. However, as the engineering of complex metabolic pathways, multi-trait stacks, and synthetic gene circuits expands, existing toolkits hit practical boundaries in assembly capacity and fixed grammars. To overcome these bottlenecks, we present MozClo, an expansion of the MoClo/PhytoBrick architecture. MozClo expands the standard Level 1 assembly framework to 10 positions using new L1 acceptors, end-linkers and dummy parts. We also identify and resolve a critical, sticky-end collision at L1 position 7 that has caused assembly failures during L2 cloning of large plasmids. To address commercial DNA synthesis length constraints and to lower cloning costs, we designed a universal 5-in-1 gene fragment multiplexing system. This architecture embeds up to five distinct parts flanked by orthogonal pairs of BpiI restriction sites into a single synthesized fragment, allowing them to sort independently into their respective L0 acceptor plasmids while maintaining complete modular flexibility of part types. Finally, we provide Level 2 cloning backbones with built in selection genes for common soybean transformation methods to facilitate downstream plant selection. Together, these advancements reduce DNA synthesis overhead and accelerate the construction of complex multigene payloads for plant biotechnology.

TEXT ABSTRACTCatalytic-RNA (cat-RNA) expressed from mobile DNA can record cellular events, such as the uptake of plasmids via horizontal gene transfer, by splicing a barcode onto 16S ribosomal RNA (rRNA) - a system termed RNA addressable modification (RAM). However, scaling RAM to record multiple simultaneous biological events requires large numbers of orthogonal cat-RNA whose signals reflect the biological features under investigation rather than variability arising from the barcode sequence. Here, we explore how to design orthogonal cat-RNA to record information about multiple plasmid-encoded traits in parallel. We show that cat-RNA having tRNA-derived barcodes with sequence variation in the anticodon stem-loop present greater signal consistency within Escherichia coli than mRNA-derived barcodes. When orthogonal cat-RNA designs harboring tRNA-derived barcodes were evaluated in Vibrio natriegens and Pseudomonas putida, increased variance was observed compared with Escherichia coli. Nevertheless, the signal consistency was sufficient to use these orthogonal cat-RNAs to report on the relative activities of four promoters and two origins of replication by sequencing barcoded-rRNA derived from the three organisms. These results show how RAM can be multiplexed to report on mobile DNA features in microbial communities and illustrate the importance of accounting for variability in RNA outputs when designing and interpreting multiplexed RNA barcoding data. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/738544v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@406ebaorg.highwire.dtl.DTLVardef@259751org.highwire.dtl.DTLVardef@1f1512corg.highwire.dtl.DTLVardef@8384b_HPS_FORMAT_FIGEXP M_FIG C_FIG

DNA assembly is a cornerstone of synthetic biology, enabling the construction of bespoke genetic systems for applications ranging from metabolic engineering to DNA nanotechnology. Conventional Gibson Assembly (GA), the most widely used method, relies on 5' exonucleolytic resection and elevated temperatures ([~]50 {degrees}C), which together prevent the retention of 5' modifications and restrict compatibility with temperature-sensitive functionalities. Here, we report a DNA assembly strategy, 3 exonuclease-mediated low-temperature DNA assembly (3LTDA), which generates complementary 5' overhangs while preserving 5' end integrity. This approach enables the efficient assembly of blunt-ended, 5'-functionalised DNA fragments into both linear and circular constructs at ambient temperature (21 {degrees}C), with some assembly observed at temperatures as low as 4{degrees}C. We systematically optimise reaction conditions and demonstrate that this method supports efficient plasmid re-circularisation and multi-fragment assembly, including the construction of a [~]12.5 kbp plasmid from multiple DNA components. Comparative analysis across several DNA substrates shows that, under their respective optimal conditions, this approach matches or exceeds GA performance, improving assembly efficiency by up to 12.8%. Sequence analysis confirms high fidelity with no detectable base-pairing errors across assembled junctions. Crucially, this method preserves chemically functionalised 5' termini, enabling downstream conjugation and biochemical functionality. Retention of azide and biotin modifications was verified through fluorescence imaging, bead-based co-localisation, and enzymatic activity in ELISA-based assays. This is in contrast to GA-assembled controls, which showed complete loss of functionality under comparable conditions. We further assembled 5 kbp dsDNA using 3LTDA from four independent segments, three with different fluorescence reporters, and the fourth containing a biotin group for microparticle conjugation, each on the 5 end. Under fluorescence illumination, bead-bound DNA with all three fluorescence markers were detected. Conventional GA assembled constructs, on the other hand, failed to retain the reporter groups and the fluorescent images did not show the presence of any fluorescent markers. In addition to enhanced performance, the method could also reduce reagent cost and eliminate the need for elevated temperatures, simplifying workflows and expanding the applicability of multi-functionalised DNA constructs. Collectively, this work establishes 3LTDA as a robust, low-temperature alternative to conventional GA, with advantages for applications requiring precise chemical modification, temperature-sensitive components, or deployment outside conventional laboratory environments.

Carbonic anhydrases are among the fastest known biocatalysts, reversibly facilitating the hydration of CO2 to HCO3- at rates up to 107 s-1, which warrants their investigation for industrial carbon capture technologies. However, engineering carbonic anhydrases to maintain stability under harsh industrial process conditions remains a key challenge, and sequence-to-function datasets compatible with machine learning to inform forward engineering are lacking. Here, we developed a high-throughput platform that couples cell-free gene expression with a gaseous CO2 colorimetric assay to map the fitness landscapes of carbonic anhydrases. From 96 diverse natural homologs, we identified a robust variant from the Aquificota phylum and conducted an exhaustive mutational scan and functional assessment of this enzyme at 70C and 90C, covering >99% of all single-amino acid substitutions (totaling 4,365 mutations assayed in 39,285 reactions). This biochemical landscape was used to benchmark 22 zero-shot protein fitness models and identify critical mutations that improved enzyme stability at 90C by more than three-fold. We then used both zero-shot protein language models and supervised learning to filter 419 model-generated variants from a ProteinMPNN library of 100,000 sequences, leading to a best-in-class enzyme that retained activity after incubation at 95C. This work demonstrates that integrating cell-free enzyme engineering with machine learning enables opportunities for high-throughput experimental measurements to benchmark and improve protein language models, accelerate design loops, and expand functional exploration within protein families where experimental information is limited.

Optogenetic control enables light-actuated regulation of gene expression and provides a programmable interface between living cells and electronic systems. However, routine prototyping of optogenetic constructs remains limited by infrastructure. Existing closed-loop platforms often require chemostats, microfluidics, robotic handling, or custom optical sensors, which can increase cost, reduce accessibility, or constrain measurement performance. Here, we present LEMOS 2.0, an updated LED-Embedded Microplate for Optogenetic Studies, a low-cost device for optogenetic stimulation and gene-circuit characterization inside standard off-the-shelf microplate readers. LEMOS 2.0 builds on the original LEMOS platform by increasing throughput from 16 to 32 microwells and reducing light leakage between adjacent microwells, allowing dark conditions to be used as an additional illumination state. The device consists of a 3D-printed frame, individually addressable LEDs positioned next to each microwell, a rechargeable battery, and an onboard microcontroller for Bluetooth-based wireless communication. Biocompatible polydimethylsiloxane microwells are cast directly into the device by replica molding, allowing bacterial cultures to be stimulated while optical density and fluorescence are measured by the microplate reader. This protocol describes the full LEMOS 2.0 workflow, including device fabrication, circuit assembly, Arduino programming, PDMS microwell casting, plate-reader setup, strain and culture preparation, automated experiment execution, device cleanup, and fluorescence/OD600 data analysis. As a demonstration, the protocol uses the CcaSR optogenetic system, in which sfGFP expression is activated by green light and repressed by red light. LEMOS 2.0 is intended to make optogenetic perturbation and gene-expression characterization more accessible to wet-lab users, enabling faster design-build-test-learn cycles without requiring specialized bioreactor or microfluidic infrastructure.

Transcriptional termination efficiency is considered an important parameter for fine tuning bacterial gene expression. Still, the design principles that determine transcription termination efficiency remain poorly understood. In this study, we aimed to investigate the impact of the 3' untranslated region (3'UTR) on gene expression in Escherichia coli and other bacteria. First, 3'UTR variant sequences were generated, with randomized 30 bp sequences inserted between the STOP-codon and an intrinsic terminator, consisting of a GC-rich hairpin and a downstream poly(U)-tail. Using three reporter genes, it was found that different 3'UTR sequences resulted in an up to five-fold difference in protein production, independent of the upstream coding sequence. The highest protein production was achieved when an adenosine was present directly upstream of the terminator hairpin. This was consolidated by systematic substitution of key nucleotides of the terminator and assessing their effect on mRNA and protein levels. Subsequently, we developed a predictive random forest machine learning model trained on the termination efficiency of different natural and synthetic terminator sequences, revealing an important role for the nucleotides directly upstream of the terminator hairpin. Altogether, this study showed that an additional adenosine nucleotide upstream of the terminator hairpin leads to improved protein production while reducing terminator read-through.

For structural-biology and protein-production pipelines, the hardest part of a difficult protein is not the biology -- it is obtaining a well-behaved sample for functional studies. Programs routinely stall at construct design, expression, and purification: deciding where to truncate, which tags to use, how to express, and how to purify so the protein survives concentration and handling. These decisions are still made largely by literature precedent and experimental experience, and they require trial-and-error before arriving at a functional construct for hard targets. We present a prospective, single-pair wet-lab case study testing whether an integrated computational platform can improve these decisions. For human fibroblast growth factor 21 (FGF21) -- a clinically important and stability-challenged metabolic hormone -- we compared two expression constructs produced side by side under the same experimental workflow, using two different design strategies: one designed by a scientist from the literature (reproducing the published core-domain construct, PDB 6M6E), and one designed by the Orbion platform -- an AI, prediction-guided protein-design system (orbion.life) -- which additionally generated the expression and purification protocols (executed scientist-in-the-loop). The platforms construct used an unconventional, longer C-terminal boundary not found in public sequence databases. Since the two constructs differ in more than one feature, we treat them as workflow-level designs throughout. The scientist construct gave a higher initial yield ([~]2.4 xmore protein recovered at affinity capture). The platform-designed construct, however, showed a more favourable downstream developability profile: it concentrated higher (1.4 vs 0.7 mg/mL) while remaining more monodisperse by dynamic light scattering (DLS). The scientist construct, in contrast, aggregated on concentration, so its initial-yield advantage did not survive: in the final concentrated sample the Orbion construct provided the more usable material for downstream studies. Computed for the mammalian host used, the platform had prospectively scored its own design higher (composite 68.7 vs 59.0 for the scientist-designed construct), and its predictions of yield, solubility, and disorder matched the wet-lab outcome. This is a single, deliberately scoped case study, not a population-level benchmark; the two constructs differ in more than one feature, and biological activity was not assayed. Alongside the bottlenecks of this approach discussed here, used as a decision aid, prediction-guided construct and protocol design has the potential to remove costly iteration cycles of protein production campaigns.

Engineering heterologous utilization of substrates requires selection of catabolic pathways that balance strain performance and product biosynthesis. Here, we compare the oxidative and isomerase arabinose utilization pathways in Pseudomonas putida strains engineered for cis,cis-muconic acid production from glucose and xylose. Based on the point of entry into central carbon metabolism, we hypothesized that the oxidative arabinose pathway would enable higher productivity while the arabinose isomerase pathway would enable higher muconate yield. In both strains, additional modifications were engineered to improve muconic acid production including sugar transporter tuning, catechol 1,2-dioxygenase overexpression, a feedback-resistant DAHP synthase, and a flux-stabilizing gltA variant. Consistent with our hypothesis, the oxidative arabinose pathway supported faster growth and higher productivity (0.58 g/L/h), whereas the arabinose isomerase pathway improved carbon efficiency, achieving muconate yields of up to 50 C-mol% in fed-batch bioreactors. Process modeling indicates that these performance metrics can reduce the minimum selling price of muconate-derived adipic acid to $2.74/kg and greenhouse gas emissions to 1.31 kg CO2e/kg, approaching cost parity and reducing emissions by 86% relative to fossil carbon-derived adipic acid. Overall, this study presents a systematic comparison of sugar catabolic pathways that enabled development of strains suited for the tradeoffs between rate and yield.

Thermostable DNA polymerases are indispensable tools in molecular biology, yet enzymes from the most extreme hyperthermophiles remain largely uncharacterized. Here, we report the biochemical and structural characterization of a family B DNA polymerase from Pyrolobus fumarii A1 (Pyrfu pol), one of the most thermoresistant archaea described to date. The enzyme was efficiently overproduced in E. coli Rosetta 2(DE3)[pLysS] and purified to homogeneity using a two-step protocol that combined heat treatment with immobilized metal affinity chromatography (IMAC). Bioinformatic analysis confirmed the canonical family B architecture, while AlphaFold-based structural modeling and comparative analysis with mesophilic RB69 DNA polymerase revealed a well-conserved structural core alongside thermoadaptive features. Radiolabel incorporation assays demonstrated enzymatic activity over a broad ionic strength range and an absolute requirement for Mg ions. PCR-based optimization confirmed these findings and revealed broad pH tolerance (6.5-11.0). Notably, Tris inhibited radiolabel-based assays (pH 7.0) yet proved essential for efficient PCR amplification (pH 8.5), suggesting a context-dependent role of buffer composition in polymerase activity. Processivity assays confirmed amplification of DNA fragments up to approximately 8,000 bp. Replication fidelity, assessed by the lacZ-based assay, showed a 2.9-fold improvement over Taq polymerase. Urea-nanoDSF yielded an exceptional melting temperature of 105.9 {+/-} 0.08 {degrees}C. Pyrfu pol also demonstrated tolerance to common PCR inhibitors, highlighting its potential utility in molecular biology applications.

BackgroundThe corn smut fungus Ustilago maydis is an important microbial model organism representing a genetically amenable and readily cultivable basidiomycete. Research in this fungus addresses a broad range of fundamental questions and its biotechnological exploitation is on the rise. Although genetic engineering in principle is well established, efficient methodology for synthetic biology approaches such as metabolic engineering or pathway transplantation has remained limited. ResultsHere, we present a comprehensive toolbox for U. maydis based on modular cloning and the characterization of more than 20 promoters. Careful comparative evaluation of insertion loci and terminator as well as reporter effects was conducted and a novel color-based strategy for straightforward genome integration was implemented. Moreover, the cloning and subsequent one-step integration of four transcriptional units into U. maydis was demonstrated by creating a "rainbow" strain producing four fluorescent proteins. ConclusionOverall, this next generation toolkit strongly advances genetic engineering and systems biology approaches in U. maydis, fostering its development into a valuable and competitive fungal chassis and prime model, particularly in applied research.

The discovery of sensory ion channels, such as thermosensitive transient receptor potential (TRP) channels and mechanosensitive PIEZOs, have transformed our understanding of mammalian sensory biology. However, the sensory receptor landscape remains incomplete, as many physiologically relevant sensory stimuli still lack identified molecular targets. Here, we describe a novel screening strategy utilizing FM 1-43, a fluorescent marker for activity of various cation channels, with a CRISPRa library (MPCL) targeting multi-transmembrane domain proteins. We validate this method by focusing on allyl isothiocyanate (AITC) and its putative receptor TRPA1. Specifically, we show that CRISPRa-mediated overexpression of TRPA1 is sufficient for FM 1-43 labeling when co-treated with AITC. Furthermore, we show that using FM 1-43 and AITC, we can efficiently FACS enrich TRPA1-expressing cells from a pool of MPCL-expressing cells. Collectively, this presents a novel method for rapidly screening select cation-dependent sensory stimuli.

The purification of industrial enzymes typically relies on costly, multi-step chromatographic protocols. To address this, we developed a novel platform termed Coated Bacterial Enzymes (CBEs), which enables one-step purification and immobilization of recombinant proteins fused to the SlpA cell wall binding domain. As a proof of concept, we used a {beta}-galactosidase from Bifidobacterium bifidum of dairy relevance. The chimeric enzyme BbgII-SlpA was expressed in Escherichia coli and captured from crude lysate onto glutaraldehyde-inactivated Bacillus subtilis cells via SlpA domain. Binding was characterized by a dissociation constant (Kd) of 16.2 {micro}M and maximum binding capacity (Bmax) of 144 {micro}mol/g. The resulting CBE biocatalyst exhibited optimal activity at pH 6.0 for ONPG and lactose, with a broader pH profile than the free enzyme. Optimal temperatures were 60 {degrees}C for ONPG and 50 {degrees}C for lactose, and CBE retained >80% activity after 390 min at 45 {degrees}C, compared to 20% for the free enzyme. Catalytic efficiencies (kcat/Km) were 2.62 x106 M-1{middle dot}s-1 for ONPG and 4.40 x102 M-1{middle dot}s-1 for lactose. Moreover, CBE showed improved tolerance to cations such as Ca2+ and Fe2+. These results suggest that the CBE platform offers a cost-effective alternative for producing high-purity, immobilized enzymes for diverse industrial bioprocesses.

Compact tissue-specific promoters are highly desirable for gene therapy because viral vectors possess limited packaging capacity. However, existing promoter engineering strategies rely primarily on rational design or de novo sequence generation and lack efficient approaches for compressing long native promoters while preserving regulatory specificity. Although genome foundation models have substantially improved sequence-to-function prediction, they have not been effectively translated into computational platforms for promoter engineering. Here, we present VirEvo, a computational promoter engineering framework that integrates a virtual dual-luciferase assay (VirDLA), genome-foundation-model-guided genetic evolution, and an orthogonal Pan-Tissue Consistency Filter (PTCF). VirDLA introduces an internal-reference normalization strategy inspired by dual-luciferase reporter assays, enabling relative comparison of promoter activity across tissues without retraining AlphaGenome. Guided by these normalized activity scores, VirEvo iteratively optimizes promoter selectivity, off-target activity, and sequence length. Using the human p16INK4a promoter as a proof of concept, VirEvo evolved a compact synthetic promoter, SRP2M, of only 398 bp, representing an 85.9% reduction in sequence length. Experimental validation using dual-luciferase reporter assays in senescent IMR90 fibroblasts demonstrated that SRP2M retained 77% of wild-type senescence selectivity while reducing basal leakage to 52% of the wild-type level. Together, these results demonstrate the feasibility of genome-foundation-model-guided promoter engineering. VirEvo provides a generalizable framework for designing compact tissue-specific regulatory elements and extends the application of genome foundation models from functional prediction to synthetic regulatory engineering.

Isothermal nucleic acid amplification tests enable rapid and decentralized molecular diagnostics but often lack robust quantitative readouts compared to quantitative PCR. Here, we present a semi-quantitative nucleic acid measurement approach using machine learning to extract spatiotemporal features from real-time fluorescence imaging of rapid isothermal amplification reactions in microfluidic chips. A convolutional neural network was trained on multiple images sampled throughout a chip-based recombinase polymerase amplification reaction to classify samples into clinically relevant or logarithmically spaced concentration ranges spanning five orders of magnitude. The clinical classification model achieved 94.6% accuracy, and the logarithmic model achieved 92.7% accuracy, with most errors occurring between adjacent concentration categories. By learning spatiotemporal patterns of fluorescence development rather than relying on explicit feature extraction, the model remained accurate at both high and low nucleic acid concentration regimes where other quantitative isothermal molecular tests struggle. This approach enables automated interpretation of amplification reactions and extends the usable dynamic range of the assay. These results demonstrate that integrating machine learning with image-based amplification methods can support rapid semi-quantitative molecular testing and may facilitate broader deployment of nucleic acid diagnostics outside centralized laboratory settings. Author summaryMany rapid nucleic acid testing methods for infectious diseases are simple to run but struggle to measure how much genetic material is present, which limits their usefulness in clinical decision-making. In our work, we study a technique that produces visible fluorescent patterns during nucleic acid amplification reactions. Traditionally, the amount of nucleic acids present are measured by counting individual bright spots, but this becomes difficult when the target nucleic acid concentration is high and the spots merge together. We developed a machine learning approach that models how the fluorescence pattern changes over time. By analyzing a sequence of images from each reaction, our model can assign samples to concentration ranges across a wide span. This allows us to extract meaningful information even when traditional analysis methods break down. Because this approach works with simple imaging systems and does not require complex equipment, it could help support more informative and accessible diagnostic testing in point-of-care and low-resource settings.

Muconic acid is a versatile platform chemical that can be biologically produced from lignocellulosic substrates, including from lignin-related aromatic compounds. Pseudomonas putida has been previously engineered to convert lignin-related aromatic compounds to muconate at quantitative molar yields. This high atom efficiency requires a supplemental carbon and energy source to support bacterial growth, and central carbon metabolic efficiency and its interaction with aromatic catabolism are underexplored. Here, we applied proteomics, metabolomics, and 13C-fluxomics to quantitatively compare central carbon and energy metabolism in wild-type P. putida KT2440 and a muconate-producing strain, P. putida CJ781. During cultivation on glucose and 4-hydroxybenzoate, CJ781 showed increased glucose uptake, reconfigured central fluxes, and increased extracellular leakage of aliphatic acids relative to wild type. These altered fluxes supported a 3-fold higher ATP pool, in excess of demand. Pyruvate and acetate secretion in CJ781 was mitigated by debottlenecking TCA-cycle entry via citrate synthase overexpression. Furthermore, tuned expression of the catechol dioxygenase and protocatechuate decarboxylase enabled the production of 36.3 g L-1 muconate at 1.1 g L-1 h-1. Overall, this work reveals how P. putida redirects carbon and energy fluxes to support aromatic bioconversion for improved bioproduction from renewable feedstocks.

Cas9 precision editing is increasingly predictable because guide, donor and target-context effects have been systematically characterized. Extending this framework to other nucleases is essential for installing variants outside convenient Cas9 target space. Cas12a provides a T-rich protospacer-adjacent motif (PAM) alternative, but determinants of efficient donor-templated Cas12a editing remain poorly defined. Here, we systematically dissected Cas12a precision editing in Saccharomyces cerevisiae across nuclease, direct repeat, expression, crRNA, donor, genomic context and time-course variables. Reporter and amplicon-sequencing assays showed that cleavage activity alone did not predict precise editing. Highly active configurations often reduced viability or lost edited alleles over time, whereas attenuated configurations better preserved programmed edits. Enhanced AsCas12a edited rapidly and tolerated shorter crRNAs, resulting in a narrower editing window, while an attenuated FnCas12a configuration edited more slowly but maintained higher viability and better distal-edit recovery. Alternative repair outcomes were rare, target-dependent, and further suppressed by LexA-FHA donor recruitment. To define design parameters at scale, we established a pooled Cas12a platform with 530 barcoded edit cassettes and recovered programmed edits for 70.2% of designs. Successful editing was reduced with TTTG PAMs, a C upstream of the PAM and at distal edit positions. Excluding these features increased the edited fraction to 85.4% and adding high predicted cleavage scores further elevated it to 91.4%. Applied retrospectively, these criteria also identified poorly edited loci in the targeted panels. Together, these data define design principles for Cas12a-mediated precision editing and establish a scalable platform for genome-scale pooled variant engineering and phenotyping in yeast.

CRISPR knockout (CRISPRko) and CRISPR interference (CRISPRi) are two workhorse technologies for loss-of-function studies, yet direct comparisons between the two are scant relative to their widespread adoption. Here, we establish benchmarking libraries for Cas9-based CRISPRko and CRISPRi screens using Perturb-seq as the read-out. For both modalities, we observe consistent transcriptional signatures among cells with the same genes perturbed, strong evidence of on-target signal. We also examine tradeoffs between modalities: while CRISPRi guides demonstrate heightened rates of off-target activity, we also observe artifacts stemming from the cellular response to double-stranded breaks with the use of CRISPRko. The libraries and analyses presented here will be a useful benchmarking and de-risking resource for any group preparing for a large-scale Perturb-seq screen.

Plant genetic transformation technologies are essential for functional genomics and genome engineering in plants. While transient expression systems offer a rapid alternative to stable transformation, existing platforms are often constrained by low efficiency, technical complexity, and limited scalability. Here, we developed AgroGem, an efficient Agrobacterium-mediated transient transformation system utilizing a geminiviral replicon-based T-DNA vector for Arabidopsis and Brassicaceae species. AgroGem significantly outperformed existing transient approaches, including AGROBEST and protoplast-based assays, in CRISPR-mediated editing efficiency. Moreover, AgroGem recapitulated the mutation spectra and chromatin accessibility-dependent editing patterns observed in stable transformation across both Cas9 and Cas12a systems, indicating that it captures genome editing outcomes in native chromatin contexts. Leveraging this capability, we performed high-resolution profiling of CRISPR-induced mutation outcomes across a panel of DNA repair mutants and identified distinct repair signatures, including unexpected roles for KU80 and XRCC4 in regulating non-homologous end joining (NHEJ). AgroGem also supported bimolecular fluorescence complementation assays for protein-protein interaction studies in Arabidopsis and was readily adapted to plate-based formats for high-throughput applications. Together, these results establish AgroGem as a robust, scalable, and versatile platform for genome editing, DNA repair analysis, and functional genetics in plants.

Here we introduce OpenEvo, a fully open-source, low-cost turbidostat platform for automated continuous culture and directed evolution experiments. Existing tools are expensive, complex, or lack open-source hardware; OpenEvo addresses this gap. OpenEvo is a complete, fully automated evolution platform with detailed, illustrated construction instructions for beginners, open-source software and firmware, and a single device priced around $300. An optional PC-based version offers enhanced functionality, including remote access, programmable evolution cycles, programmable LED stimulation, and a data visualization tool. OpenEvo can cycle through three types of media for positive, negative, and neutral selection conditions, supporting a wide range of experimental designs. We validate the use of OpenEvo by evolving H. volcanii to grow from 15% to 12% salt over ~150 cycles, ~1,000 hours. Evolved cells grew 36% faster than wild-type at 12% salt. Whole-genome sequencing of adapted cells found SNPs and large deletions. We also demonstrate positive and negative selection using the OpenEvo LEDs to drive optogenetics via a Phytochrome B-based optogenetic tool, with light as the selection stimulus during over 4000 hours of growth. OpenEvo lowers the technical and cost barriers for continuous evolution experiments, serves as a teaching tool, and is designed to grow an open community of users who share modifications.