Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.64898/2026.06.11.731564

UstiGate: Next generation toolkit for advanced genetic engineering of the basidiomycete chassis Ustilago maydis

Hasenklever, J. C.·Paderi, V.·Hasenklever, D.·Axmann, I. M.·Schipper, K.
View original source ↗Export metadata ↓

Abstract

The corn smut fungus Ustilago maydis is an established model for fungal biology and an emerging host for biotechnology. However, its broader application in synthetic biology has been constrained by a limited repertoire of standardized genetic parts and tools for multigene engineering. Here, we introduce UstiGate, a modular toolkit that combines MoClo-compatible DNA assembly with targeted genomic integration in U. maydis. The toolkit comprises 92 parts and vectors, including more than 20 promoter regions as well as terminators, selectable markers, fluorescent reporters and modules for different genomic integration sites. Quantitative reporter analyses at both, population and single-cell level, revealed a broad range of promoter strengths and characterized their behavior across growth phases, media, genomic loci and reporter contexts. We further identified a maltose-inducible, glucose-repressed promoter that enables autoinduction and established carotenoid-biosynthesis genes as integration sites supporting visual pre-selection of transformants. Finally, UstiGate enabled the assembly and simultaneous genomic integration of four transcriptional units in a single transformation. UstiGate thus provides a standardized and quantitatively characterized platform for standard applications as well as multigene engineering, enabling advanced synthetic biology applications such as pathway transplantation in U. maydis.

Explore related subjects

synthetic biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Hasenklever, J. C., Paderi, V., Hasenklever, D., Axmann, I. M., Schipper, K.. 2026-07-08. UstiGate: Next generation toolkit for advanced genetic engineering of the basidiomycete chassis Ustilago maydis. https://doi.org/10.64898/2026.06.11.731564

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Gene expression noise is reduced in communicating synthetic cell populations

A major goal in bottom-up synthetic biology is the construction of multicellular synthetic systems capable of coordinated and robust collective behaviours. However, robustness is often limited by noise and variability arising from increased molecular complexity. Whilst communication has been implemented in synthetic multi-cellular systems, the ability for communication to suppress cell free gene expression variability in populations of synthetic cells remain unexplored. To address this, we encapsulated the Lux and Las quorum sensing gene circuits in lipid vesicles under cell-free conditions to test the effect of communication on reducing cell-free gene expression variability across the population. Our results show that communication, limiting expression resources, and membrane surface effects can reduce gene expression variability. Resource limited Gillespie simulations for transcription and translation show that communication-mediated coupling reduces population-level expression noise under constrained and excess resource conditions. Together, our work provides simple strategies to reduce gene expression variability and thereby improve robustness in synthetic multicellular systems, an important criteria for the future applications of synthetic cells.

synthetic biology↗
bioRxiv2026

Boolean Logic-responsive FRET Biosensors via Genetically Encoded Autonomous Compilation

Forster resonance energy transfer (FRET) is commonly used to monitor protein-protein interactions in situ. The high spatiotemporal resolution and facile implementation inside complex molecular environments have spearheaded FRET's widespread adoption in biosensing. Despite these advantages, current FRET biosensors are largely restricted to the detection of the presence/absence of individual inputs and are thus unable to sense several multiplexable inputs simultaneously within complex milieu of biological environments. In this work, we introduce a generalizable strategy to construct genetically encoded protein-based FRET biosensors capable of recognizing multiple inputs following Boolean logic-type (YES/OR/AND) operations. These topologically specified FRET sensors powerfully expand the input capacity in sensing protein-protein interactions while providing a user-programmable platform for monitoring heterogeneous biological activities both in vitro and in living cells.

synthetic biology↗
bioRxiv2026

AI-Guided Multi-Objective Engineering of Glucoamylase Enables Acidification-Free Starch Saccharification

Glucoamylase is essential for industrial starch saccharification, but the limited thermostability and near-neutral pH tolerance of fungal glucoamylases necessitate cooling and acidification of liquefied starch. Here, we developed an artificial intelligence-guided strategy to simultaneously improve the thermostability, pH tolerance, and catalytic activity of glucoamylase from Penicillium oxalicum (PoGA). Two property-specific machine-learning models, CASPE-T and CASPE-A, identified substitutions associated with thermostability and pH tolerance, respectively. Experimental screening identified beneficial substitutions in 11 of 21 CASPE-T and 12 of 22 CASPE-A candidates. Folding-energy-guided recombination integrated the two traits while maintaining structural compatibility. The optimal variant, PoGA T513E/Q305N, exhibited 2.21-fold higher specific activity than the wild type, with half-life extended from 22.3 to 57.9 min at 60 degrees C and from 16.6 to 64.7 min at pH 8.0. Molecular dynamics simulations attributed these improvements to reinforcement of high-occupancy hydrogen-bonding networks, suppression of conformational fluctuations in the linker and carbohydrate-binding module, enhanced long-range dynamic coordination, and preservation of a compact catalytic architecture. At 60 degrees C and pH 6.5 without acidification, PoGA T513E/Q305N produced 219.9 g/L glucose and achieved 89.1% starch conversion, 31.4% higher than the wild type. This work provides an efficient framework for multi-objective enzyme engineering and sustainable starch biorefining.

synthetic biology↗