Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2021.05.25.445608

Increased biosynthesis of acetyl-CoA in the yeast Saccharomyces cerevisiae by overexpression of a deregulated pantothenate kinase gene

Olzhausen, J.·Grigat, M.·Seifert, L.·Ulbricht, T.·Schueller, H.-J.
View original source ↗Export metadata ↓

Abstract

Coenzyme A (CoA) and its derivatives such as acetyl-CoA are essential metabolites for several biosynthetic reactions. In the yeast S. cerevisiae, five enzymes (encoded by essential genes CAB1-CAB5; coenzyme A biosynthesis) are required to perform CoA biosynthesis from pantothenate, cysteine and ATP. Similar to enzymes from other eukaryotes, yeast pantothenate kinase (PanK, encoded by CAB1) turned out to be inhibited by acetyl-CoA. By genetic selection of intragenic suppressors of a temperature-sensitive cab1 mutant combined with rationale mutagenesis of the presumed acetyl-CoA binding site within PanK, we were able to identify the variant CAB1 W331R, encoding a hyperactive PanK completely insensitive to inhibition by acetyl-CoA. Using a versatile gene integration cassette containing the TPI1 promoter, we constructed strains overexpressing CAB1 W331R in combination with additional genes of CoA biosynthesis (CAB2, CAB3, HAL3, CAB4 and CAB5). In these strains, the level of CoA nucleotides was 15-fold increased, compared to a reference strain without additional CAB genes. Overexpression of wild-type CAB1 instead of CAB1 W331R turned out as substantially less effective (4-fold increase of CoA nucleotides). Supplementation of overproducing strains with additional pantothenate could further elevate the level of CoA (2.3-fold). Minor increases were observed after overexpression of FEN2 (encoding a pantothenate permease) and deletion of PCD1 (CoA-specific phosphatase). We conclude that the strategy described in this work may improve the efficiency of biotechnological applications depending on acetyl-CoA. Key pointsO_LIA gene encoding a hyperactive yeast pantothenate kinase (PanK) was constructed. C_LIO_LIOverexpression of CoA biosynthetic genes elevated CoA nucleotides 15-fold. C_LIO_LISupplementation with pantothenate further increased the level of CoA nucleotides. C_LI

Source connections

Explore related subjects

bioengineeringPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Olzhausen, J., Grigat, M., Seifert, L., Ulbricht, T., Schueller, H.-J.. 2021-05-26. Increased biosynthesis of acetyl-CoA in the yeast Saccharomyces cerevisiae by overexpression of a deregulated pantothenate kinase gene. https://doi.org/10.1101/2021.05.25.445608

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

KEEP EXPLORING

Related preprints

bioRxiv2026

Synergy-informed bilevel optimization reveals joint-specific benefits for realistic exoskeleton torque prediction

Simulation-driven optimization can guide exoskeleton control design, but its utility is limited by the accuracy with which muscle coordination is predicted. Strict effort-minimization formulations predict non-physiological muscle shutdown under high exoskeleton assistance, leading to peak assistive torques that exceed values reported in human-in-the-loop experiments. We evaluated the accuracy of synergy-informed simulations at predicting assistance across four single-joint exoskeleton configurations: ankle plantarflexion, knee extension, hip flexion, and hip abduction. We implemented a bilevel optimization to predict a parameterized assistive torque that minimizes metabolic cost, with assisted muscle dynamics estimated via either effort-minimization simulations (minimizing muscle effort only) or synergy-informed simulations (minimizing muscle effort constrained to a synergy structure). We used experimental data from five unimpaired adults walking at their preferred speed and compared results descriptively between the two formulations within each subject. Assistance based on effort-minimization simulations shut down agonist muscle activations and overestimated peak assistive torque compared with experimental values. In contrast, constraining muscle controls to a synergy structure prevented non-physiological muscle shutdown and yielded assistive torques closer to those measured in human-in-the-loop experiments. This benefit was not observed equally across all assisted degrees of freedom or subjects, emerging only where no single synergy could be suppressed to unload the assisted muscles. Synergy weights can therefore be interpreted as joint-specific predictors of when simulations can reliably inform wearable robot design.

bioengineering↗
bioRxiv2026

Engineered microvessel networks -- Longitudinal transcriptomic profiling validates chip-grown tissues as a robust model for studying vasculature

Vascularised Organ-on-Chip (OoC) models are promising New Approach Methodologies (NAMs), but their translation requires validation for defined Contexts of Use (CoU). Here, we combine microfluidic microvessel networks (MVNs) with longitudinal bulk and single-cell RNA sequencing to determine how cell provenance influences engineered vascular phenotype. Stromal cell identity produced distinct network architectures and transcriptional trajectories, demonstrating that support cells, commonly treated as interchangeable, represent an important CoU variable. Primary human pancreatic microvascular endothelial cells failed to form stable perfusable networks, but supplementation with 10% Human Umbilical Vein Endothelial Cells (HUVECs) or Blood Outgrowth Endothelial Cells (BOECs) rescued self-assembly. Single-cell transcriptomics identified specialised endothelial populations associated with vascular morphogenesis, including tip, stalk, phalanx, endothelial to mesenchymal transition (EndMT) and pericyte-like endothelial cells. Failed networks lacked coherent endothelial specialisation, whereas rescued networks restored stabilising cell states and revealed FLRT2--UNC5B signalling within pericyte-like HUVECs, recapitulating a pathway implicated in angiogenic development in vivo. These findings establish cell provenance as a critical determinant of microvascular NAM performance and demonstrate how transcriptomic validation can define and strengthen the biological relevance of microvessel-on-chip models for specific CoUs.

bioengineering↗
bioRxiv2026

Benchmarking foundation models for resting-state functional magnetic resonance imaging time series in cognitive aging research

Foundation models trained on large neuroimaging datasets could help smaller studies investigate cognition from brain recordings. However, whether the foundation model-derived representations improve assessment of current cognition, prediction of follow-up cognition, or characterization of cognitive change remains unclear. We evaluated nine configurations from five model families that process regional resting-state functional magnetic resonance imaging time series, using 3,103 scans from 1,653 participants across two observational and five intervention aging cohorts. Primary frozen representations showed no consistent superiority over conventional functional connectivity for concurrent cognitive associations or diagnostic classification. Changing the readout improved selected concurrent cognitive associations without updating model weights, indicating that performance depended partly on how representations were extracted. Additional post-training and embedding alignment yielded gains in selected settings but did not consistently improve performance across outcomes. In the primary longitudinal analyses, imaging representations did not establish added value beyond baseline clinical measures. These findings show that readout choice influences concurrent cognitive associations, while the added value of these representations for longitudinal outcomes remains unestablished.

bioengineering↗