Biology subjects

Donati, S.

Publications and source records attributed to Donati, S..

12 recordsLinked to original sources

bioRxiv2026

Adaptive laboratory evolution rewires Pseudomonas putida for resource-efficient acetate assimilation

Acetate is an attractive renewable two-carbon substrate for microbial biotechnology, but its toxicity limits growth and carbon-use efficiency at process-relevant concentrations. Here, we used adaptive laboratory evolution to improve acetate tolerance in a genome-reduced strain of Pseudomonas putida and combined whole-genome sequencing, reverse engineering, transcriptomics, proteomics, and 13C-acetate fluxomics to resolve the underlying adaptation mechanisms. Evolution under increasing acetate concentrations selected recurrent mutations in gacA and fabB, which encode a global response regulator and a fatty acid biosynthesis enzyme, respectively. Reverse engineering of these mutations recovered most of the evolved phenotype, including shorter lag phase and substantially higher biomass yield from acetate. Multi-omic analyses showed repression of type VI secretion systems, carbohydrate storage functions, fatty acid metabolism, and oxidative stress-associated proteins, indicating resource reallocation away from costly stress and non-essential programs. Fluxomics further revealed reduced EDEMP cycling and increased glyoxylate shunt flux, consistent with improved acetate-carbon retention in biomass. These results establish acetate tolerance in P. putida as a resource-efficiency phenotype and identify gacA and fabB as actionable targets for acetate-based bioproduction.

synthetic biology↗

bioRxiv2026

Seven mutations unlock strict synthetic methylotrophy in engineered Pseudomonas putida

Methanol is a reduced, soluble one-carbon (C1) feedstock for sustainable bioproduction, but converting this potential into robust microbial growth remains difficult. Several synthetic C1 assimilation routes depend on autocatalytic cycles, whose operation requires coordinated control of redox balance, toxic intermediates, substrate regeneration, and host regulation. Here, we implemented the serine-threonine cycle (STC) in the soil bacterium Pseudomonas putida and used growth-coupled selection with adaptive laboratory evolution (ALE) to transition from mixotrophic C1 incorporation to strict methylotrophy. The evolved strain grew with methanol as the sole carbon and energy source under atmospheric CO2 with a doubling time of ca. 40 h. Whole-genome sequencing, reverse genetics, biosensors, isotope labelling, and comparative RNA sequencing showed that evolution repeatedly targeted native pyrroloquinoline quinone (PQQ)-dependent methanol oxidation, membrane-bound transhydrogenase activity, glycine regeneration, STC enzyme balance, and global regulatory nodes. Additional ALE under glycine-methanol co-feeding increased growth rates and exposed further targets for improving cycle flux. These results establish P. putida as a chassis for strict synthetic methylotrophy and define actionable engineering routes toward C1 biomanufacturing. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=63 SRC="FIGDIR/small/739708v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1642d2dorg.highwire.dtl.DTLVardef@1d203d1org.highwire.dtl.DTLVardef@f8a5d7org.highwire.dtl.DTLVardef@4fe272_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2026

growthcurves: User-friendly tools for quality-controlled cellular growth analysis

SummaryBiological growth curves are widely used but inconsistently analyzed due to fragmented workflows and limited quality control. We present growthcurves, a Python package for extracting growth parameters, and two open-source web applications, MicroGrowth and AutoGrowth, that combine automated fitting with interactive, human-in-the-loop inspection, selective refitting and traceable export for microplate reader and mini-bioreactor datasets in batch or turbidostat cultivation mode. Availability and Implementationgrowthcurves is implemented in Python and is freely available to non-commercial users at [https://github.com/biosustain/growthcurves.git] and through PyPI at [https://pypi.org/project/growthcurves/]. MicroGrowth and AutoGrowth are available at [https://biosustain.github.io/growthcurves_app/], and their source code is available at [https://github.com/biosustain/growthcurves_app.git]. Documentation, installation instructions, example datasets and tutorials are available at [https://growthcurves.readthedocs.io/en/latest/]. Contactstefdon@dtu.dk; cargac@dtu.dk Supplementary InformationSupplementary information and Supplementary Methods are available online.

bioinformatics↗

bioRxiv2026

Automated mini-bioreactors reveal the temporal dynamics and multi-omics responses of CRISPRi knockdowns in Pseudomonas putida

Characterizing CRISPR interference (CRISPRi) phenotypes presents a fundamental temporal challenge: pre-existing overabundance of target proteins can mask early silencing, requiring extended growth for dilution, yet prolonged repression rapidly selects for escaper mutants. To resolve this, we integrated a tightly regulated CRISPRi system in Pseudomonas putida with an automated mini bioreactor platform operating in turbidostat mode. By maintaining continuous exponential growth, we mapped the exact temporal dynamics of essential gene silencing. We identified a critical observation window between 17 and 27 hours (7-9.5 cell doublings) where repression exerts its maximum physiological impact, directly preceding population takeover by target-site mutated escapers. Applying this workflow to the arginine biosynthesis pathway, multi-omics profiling disentangled transient physiological buffering from long-term mutational events, revealing that argH and argG knockdowns trigger highly diverse metabolomic perturbations. This scalable framework overcomes batch culture limitations, ensuring precise temporal control for accurate phenotypic characterization and reliable functional genomics. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/709552v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@c6795dorg.highwire.dtl.DTLVardef@49f52dorg.highwire.dtl.DTLVardef@17f5d80org.highwire.dtl.DTLVardef@d3bbca_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

Integrated control of redox and energy metabolism by the membrane-bound and soluble transhydrogenases of Pseudomonas putida across metabolic regimes

Redox homeostasis is central to microbial physiology and stress adaptation, yet the functional roles of transhydrogenases remain poorly understood beyond a few organisms. In this study, we systematically explored how Pseudomonas putida, a model soil bacterium, integrates two distinct transhydrogenases (membrane-bound PntAB and soluble SthA) into a flexible and reversible redox-balancing system that supports metabolic robustness across diverse metabolic regimes. While single deletions of either enzyme had minimal impact on the overall fitness, the double {Delta}pntAB {Delta}sthA mutant exhibited growth defects, disrupted energy charge, and redox imbalance. Unexpectedly, SthA proved essential for acetate-dependent growth, a phenotype traced to a transcriptional regulator involved in glyoxylate metabolism. Transhydrogenases also mediated tolerance to formate, a key one-carbon (C1) substrate for biotechnology, by channeling reducing equivalents released during feedstock oxidation. Synergistic activity with native formate dehydrogenases enabled redox buffering, even under stressful conditions. Functional complementation with native and engineered NAD+- or NADP+-dependent dehydrogenases validated SthA as the main sink for excess NADH. Comparative genomics linked transhydrogenase gene neighborhoods to stress and membrane processes, highlighting their evolutionary significance. These findings redefine transhydrogenases as dynamic regulators of redox metabolism, not passive cofactor shuttles. Furthermore, this work positions P. putida as a prime host for redox-intensive applications, informing design principles for C1-based metabolic engineering. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=198 SRC="FIGDIR/small/686620v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@17c0e06org.highwire.dtl.DTLVardef@17cd094org.highwire.dtl.DTLVardef@161b5b9org.highwire.dtl.DTLVardef@1e1897e_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2025

A recursive pathway for isoleucine biosynthesis arises from enzyme promiscuity

Enzyme promiscuity can be the starting point for the evolution of new enzymatic activities and pathways. Previously Cotton et al. (2020) identified underground isoleucine biosynthesis routes that can replace the canonical route in Escherichia coli, after they deleted the enzymes that catalyze the formation of its precursor 2-ketobutyrate. Using this strain and short-term evolution we identify a new pathway for isoleucine biosynthesis based on the promiscuous activity of the native enzyme acetohydroxyacid synthase II. We demonstrate that this enzyme catalyzes the previously unreported condensation of glyoxylate with pyruvate to generate 2-ketobutyrate in vivo. The gene encoding this enzyme, ilvG, is inactivated by a frameshift mutation in the laboratory model strain E. coli K-12 MG1655. Its evolutionary reactivation we report here points to a potential natural role in isoleucine biosynthesis in E. coli. Isoleucine biosynthesis proceeds with a further condensation step of 2-ketobutyrate with pyruvate, again catalyzed by AHAS, giving the proposed pathway the unusual property of recursivity. The discovered enzyme activity uses glyoxylate and pyruvate as direct central metabolic precursors for isoleucine biosynthesis instead of its canonical indirect biosynthesis via the amino acid threonine. Unlike previously discovered underground isoleucine routes by Cotton et al., this route is more likely to play a role in natural isoleucine biosynthesis in E. coli due to the use of ubiquitous metabolites and its activity in aerobic conditions. The discovered route further expands the known metabolic space for isoleucine biosynthesis in E. coli and potentially other organisms, and could find applications in biotechnological isoleucine production.

microbiology↗

bioRxiv2025

A Robust Isotope Ratio LC-MS/MS Workflow for High-Throughput Metabolic Profiling of Bacteria

Stable isotope dilution mass spectrometry (IDMS) has become a cornerstone of quantitative metabolomics, enabling accurate intracellular metabolite quantification across a range of biological systems. However, the broader adoption of IDMS in high-throughput studies remains limited by the high costs of commercially available 13C-labeled internal standards (IS), labor-intensive in-house IS production, and the narrow applicability of existing methods to different organisms. Here, we present a robust and scalable IDMS-based LC-MS/MS workflow for high-throughput metabolic profiling of diverse bacteria. The analytical method couples ion-pairing liquid chromatography with multiple reaction monitoring (MRM) to quantify 96 intracellular metabolites in under 16 minutes, with an average RSD of 21%. We developed a protocol for large-scale production of high-quality 13C-labeled IS, considerably lowering the cost for high-throughput IDMS studies. We then applied the workflow to 5 bacterial species in different cultivation conditions. This work provides a versatile platform for microbial metabolomics, supporting systems biology and data-driven metabolic engineering at scale. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/669109v2_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1f3e9e9org.highwire.dtl.DTLVardef@81eb0eorg.highwire.dtl.DTLVardef@16efe09org.highwire.dtl.DTLVardef@1e83a06_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2025

Parageobacillus thermoglucosidasius and the reductive glycine pathway: A journey of Almosts and Maybes.

We aimed to engineer the reductive glycine pathway (rGlyP) in Parageobacillus thermoglucosidasius for synthetic assimilation of formate and methanol via a mixed rational and evolutionary approach. We attempted to obtain glycine or serine auxotrophic strains in P. thermoglucosidasius as a starting point to impose a selective pressure and engineer formate assimilation via the rGlyP. While serine auxotrophy was partially achieved via gene deletion of serA, alternative glycine biosynthesis routes limited its stringency, and glycine auxotrophy could not be obtained due to unsuccessful genome modification. Even though formate supplementation improved the growth of the serA deficient strain, we confirmed that formate was not assimilated into biomass via 13C-labeling experiments. Thus, we hypothesized the increase in growth of the serA deficient mutant was likely due to extra energy provided by formate oxidation, rather than biomass incorporation. We also attempted heterologous overexpression of the C1 module from Moorella thermoacetica, but this did not yield any detectable effect in growth nor formate assimilation. These findings highlight the challenges in rGlyP implementation in non-model organisms, the need for better metabolic annotation in P. thermoglucosidasius, and provide valuable insights for future engineering of synthetic C1 metabolism in thermophiles via the rGlyP.

bioengineering↗

bioRxiv2025

Comparative genomic assessment of the Cupriavidus necator species for one-carbon based biomanufacturing

The transition from a petroleum-based manufacturing to biomanufacturing is an important step towards a sustainable bio-economy. In particular biotechnological processes which use one carbon (C1) compounds as feedstock represent an interesting avenue. Many bacterial species evolved naturally to thrive on such compounds, among them Cupriavidus necator, which has been studied in the past due to its range of metabolic capabilities in utilization and production of compounds of interest. Cupriavidus necator strain H16 is the reference laboratory strain for this species and by far the most extensively studied. In contrast, research efforts and genomic characterization of other strains within this species have been limited and sporadic. Therefore, the genomic diversity and full metabolic potential across the broader species remain poorly understood. In this work, we collected publicly available genomes along with newly sequenced ones. From a collection of 44 genomes we curated a final collection of 22 genomes deemed to be C. necator. We examined hallmark metabolic functions, including carbon dioxide fixation, formate assimilation, and hydrogen utilization. We identified methylation motifs and restriction modification systems. Finally, strains ATCC 25207, TA06, and 1978 are proposed as candidate strains of interest based on their genomic make-up and observations from literature. This work provides a comprehensive genomic resource for the C. necator species, facilitating its development as a biomanufacturing platform and advancing our understanding of its metabolic diversity and potential applications. ImportanceThe green transition from petroleum-based manufacturing to a biomanufacturing economy requires new solutions. One of these is the development of bacterial platforms for production of valuable chemicals, in particular from CO2 and derived molecules. In this context, Cupriavidus necator is one of the most studied platform strains, although the genomic potential of this species has been seldom explored. This work provides a curated set of C. necator genomes, collected from public repositories and additional newly sequenced genomes. Through multiple analyses, C. necator ATCC 25207, TA06, and 1978 are proposed as strains of interest for further use. These findings lay the groundwork for advancing C. necator as a key organism in sustainable biomanufacturing, highlighting its potential for efficient carbon fixation, formate assimilation, and hydrogen utilization. The identification of methylation motifs and restriction modification systems further supports genetic engineering efforts, making these strains highly valuable for future biotechnological applications.

microbiology↗

bioRxiv2024

Awakening of the RuMP cycle for synthetic methylotrophy in the thermophile Parageobacillus thermoglucosidasius.

Given sustainability and scalability concerns of using sugar feedstocks for microbial bioproduction of bulk chemicals, widening the feedstock range for microbial cell factories is of high interest. Methanol is a one-carbon alcohol that stands out as an alternative feedstock for the bioproduction of chemicals, as it is electron-rich, water-miscible and can be produced from several renewable resources. Bioconversion of methanol into products under thermophilic conditions (>50{degrees}C) could be highly advantageous for industrial biotechnology. Although progress is being made with natural, thermophilic methylotrophic microorganisms, they are not yet optimal for bioproduction and establishing alternative thermophilic methylotrophic bioproduction platforms can widen possibilities. Hence, we set out to implement synthetic methanol assimilation in the emerging thermophilic model organism Parageobacillus thermoglucosidasius. We engineered P. thermoglucosidasius to be strictly dependent for its growth on methanol assimilation via the core of the highly efficient ribulose monophosphate (RuMP) cycle, while co-assimilating ribose. Surprisingly, this did not require heterologous expression of RuMP enzymes. Instead, by laboratory evolution we awakened latent, native enzyme activities to form the core of the RuMP cycle. We obtained fast methylotrophic growth in which [~]17% of biomass was strictly obtained from methanol. This work lays the foundation for developing a versatile thermophilic bioproduction platform based on renewable methanol.

synthetic biology↗

bioRxiv2024

Expanding the biotechnological scope of metabolic sensors through computation-aided designs

Metabolic sensors are microbial strains modified so that biomass formation correlates with the availability of specific metabolites. These sensors are essential for bioengineering (e.g. in growth-coupled designs) but creating them is often a time-consuming and low-throughput process that can potentially be streamlined by in silico analysis. Here, we present the systematic workflow of designing, implementing, and testing versatile Escherichia coli metabolic sensor strains. Glyoxylate, a key metabolite in (synthetic) CO2 fixation and carbon-conserving pathways, served as the test molecule. Through iterative screening of a compact metabolic model, we identified non-trivial growth-coupled designs that resulted in six metabolic sensors with a wide sensitivity range for glyoxylate, spanning three orders of magnitude in detected concentrations. We further adapted these E. coli strains for sensing glycolate and demonstrated their utility in both pathway engineering (testing a key metabolic module via glyoxylate) and applications in environmental monitoring (quantifying glycolate produced by photosynthetic microalgae). The versatility and ease of implementation of this workflow make it suitable for designing and building multiple metabolic sensors for diverse biotechnological applications. TeaserA streamlined workflow enables the rapid design of versatile E. coli metabolic sensors for detecting key metabolites in bioengineering and monitoring.

synthetic biology↗

bioRxiv2022

An automated workflow for multi-omics screening of microbial model organisms

Multi-omics datasets are becoming of key importance to drive discovery in fundamental research as much as generating knowledge for applied biotechnology. However, the construction of such large datasets is usually time-consuming and expensive. Automation is needed to overcome these issues by streamlining workflows from sample generation to data analysis. Here, we describe the construction of a complex workflow for the generation of high-throughput microbial multi-omics datasets. The workflow comprises a custom-built platform for automated cultivation and sampling of microbes, sample preparation protocols, analytical methods for sample analysis and automated scripts for raw data processing. We demonstrate possibilities and limitations of such workflow in generating data for three biotechnologically relevant model organisms, namely Escherichia coli, Saccharomyces cerevisiae, and Pseudomonas putida.

systems biology↗