Methylomonas sp. DH-1 is a Gram-negative methanotrophic bacterium that utilizes methane as a carbon source and presents a potential chassis for sustainable production of value-added metabolites from this greenhouse gas. Realizing this potential requires the development of reliable and tailored genetic engineering methodologies. Recent progress has expanded the molecular toolbox for this strain, including optimized transformation methods to overcome host restriction barriers and plasmid-free genome engineering using cell-penetrating Cre recombinase. In addition, a tunable promoter library for tunable transcriptional control and a synthetic small regulatory RNA platform for post-transcriptional modulation of gene expression have been established. Promising complementary engineering strategies, including adaptive laboratory evolution, synthetic consortia, and systems biology approaches can be used to improve strain robustness and metabolic performance. The review highlights these advances, along with metabolic engineering efforts that have enabled the synthesis of diverse value-added chemicals in Methylomonas sp. DH-1. Collectively, these developments provide the foundation for metabolic engineering and synthetic biology in Methylomonas sp. DH-1 and may inform the design of genetic tools in other methanotrophs.

2-phenylethanol (2-PE) is a high-value aromatic alcohol. Its bioproduction is limited by pathway bottlenecks, limited by a rate-limiting decarboxylation step, product toxicity, and volatilization. We sought to build an efficient Escherichia coli (E. coli) platform by optimizing the segment of the Ehrlich route that converts L-phenylalanine (L-Phe) to 2-PE, together with a food-grade soybean-oil overlay for in situ product recovery (ISPR). Whole-cell assays showed that phenylpyruvate decarboxylation was the main bottleneck when the yeast decarboxylase Aro10 was used. A phylogeny-guided screen identified Lactococcus lactis KivD as a superior substitute in E. coli. After replacing Aro10 with KivD and tuning expression, leveraging endogenous glutamate dehydrogenase (GDH) for NAD(P)H recycling enabled sufficient cofactor regeneration, yielding 49.5 mM 2-PE from 50 mM L-Phe with 99.0% conversion. At the shake-flask scale, a fed-batch L-Phe feeding strategy coupled with a 2:1 soybean-oil overlay for in situ product removal reduced toxicity and volatilization losses, producing 130 mM 2-PE (15.9 g/L). Using soybean oil as an ISPR phase effectively sequestered 2-PE from the aqueous phase, minimizing volatilization and increasing the overall recovered yield to 94.2% based on L-Phe consumption. Replacing the rate-limiting decarboxylation step with KivD, balancing redox through cofactor recycling, and coupling the pathway to a mild oil-overlay recovery increased flux and enabled high-titer 2-PE in E. coli. The workflow of bottleneck substitution plus biocompatible in situ recovery can be transferred to related aromatic alcohols and provides a foundation for de novo routes and high-cell-density fermentations that target still higher titers.

Magnetic resonance imaging (MRI) of breast tissue is often used to definitively diagnose breast cancer due to its high soft-tissue contrast. However, its high cost and limited accessibility make it unsuitable for real-time screening, unlike ultrasound. Machine learning models that synthesize MRI from ultrasound could enable low-cost screening and triage by providing MRI-like tissue characterization during routine ultrasound exams. However, machine learning models trained to generate synthetic MRIs from ultrasound often struggle due to the absence of paired datasets across imaging modalities. This lack of paired datasets is a particular struggle in the field of model building for medical imaging purposes. We propose a physics-based method for generating synthetic ultrasound images from MRI volumes using mathematical modeling of acoustic beam propagation and tissue composition. We use a singular MRI example as a proof-of-concept of this physics simulation, which is based on pre-existing ultrasound physics. Each MRI slice was divided into a 2 × 2 grid to identify local beam entry regions. Tangent lines were calculated along each grid edge to estimate perpendicular ultrasound beam paths in a pinwheel fashion around the breast tissue. Initial simulations indicate that the generated ultrasound-like images reproduce plausible intensity gradients and textural variation consistent with known acoustic-tissue interactions. In resource-limited settings, access to MRI for breast cancer workup remains a significant barrier when ultrasound findings are inconclusive. To enable development of cross-modal synthesis models, we present a physics-based simulation framework that creates paired MRI-ultrasound training datasets by synthesizing realistic ultrasound images from available MRI data. This supports the feasibility of using physics-driven methods to generate synthetic ultrasound from MRI data. Because contrast enhancement and vascular permeability are not modeled, this framework should be interpreted as a non-contrast anatomical MRI to conventional B-mode ultrasound simulation rather than a complete cross-modal transformation that captures DCE-MRI or contrast-enhanced ultrasound behavior.

Biological production of adipic acid, a crucial building block in nylon and polymer manufacturing, from renewable feedstocks has attracted attention as a sustainable alternative to the traditional petrochemical production. The enzymatic conversion of ε-caprolactone into adipic acid via alcohol dehydrogenase (ADH2) and aldehyde dehydrogenase (ALDH) represents a promising route due to its short pathway and high theoretical yield. To optimize this conversion route in Escherichia coli and enhance conversion efficiency, we constructed an adipic acid-responsive biosensor for high-throughput screening. By systematically optimizing the biosensor system, we achieved a 7.15-fold dynamic range. Using this biosensor system, we performed directed evolution of the low-activity ALDH and identified variants with improved conversion performance. The K23Q mutant showed a 2.33-fold increase in adipic acid conversion efficiency and subsequent fed-batch fermentation achieved 30.1 g/L of adipic acid production from ε-caprolactone with 92.7% of theoretical maximum yield. These results demonstrate the potential of biosensor-guided enzyme engineering to enhance catalytic efficiency and support the sustainable biological production of adipic acid.

Gas-phase bioprocesses that immobilize microbial cells on solid carriers enable efficient conversion of volatile or poorly water-soluble substrates. Acinetobacter sp. Tol 5 is a highly adhesive bacterium capable of utilizing various hydrocarbons, making it a promising chassis candidate for gas-phase bioprocesses. However, Gas-phase bioprocesses expose cells to fluctuating humidity and transient desiccation that can compromise viability and catalytic performance. In Gram-negative bacteria, especially in pathogens, desiccation is known to impose multifactorial stress, such as loss of cellular water and energetics, damage to DNA and proteins, oxidative stress, and disruption of the cell envelope. In contrast, for chassis strains used in or being considered for gas-phase bioprocesses, their desiccation tolerance including robustness of biocatalytic activity following humidity fluctuations and responses to desiccation stress remain incompletely defined. Here, we evaluated the viability, energy status, and gas-phase toluene degradation of Tol 5 as a chassis for gas-phase processes after controlled desiccation (8%, 52%, and > 95% RH), in comparison with Acinetobacter baylyi ADP1, Pseudomonas putida, and Escherichia coli. To minimize adhesion-related bias in post-desiccation measurements, we used an ataA-deficient Tol 5 mutant (Tol 5 ΔataA) for the assays. Acinetobacter strains maintained high viability during desiccation for 16 days, whereas P. putida and E. coli showed significant loss of viability at 8% RH and 52% RH. Intracellular ATP measurements further indicated that desiccation reduced intracellular ATP in all strains, but E. coli rapidly exhausted ATP at 8% and 52% RH, whereas Acinetobacter strains and P. putida retained intracellular ATP. In a gas-phase toluene degradation assay, immobilized Tol 5 retained higher toluene-degrading activity after desiccation than P. putida mt-2. Transcriptome profiling revealed a multilayered Tol 5 response involving DNA and RNA maintenance, cell envelope trafficking and remodeling, redox-responsive functions, and broad repression of growth-associated metabolism. Our results highlight Acinetobacter, particularly Tol 5, as a promising chassis candidate for gas-phase bioprocesses and suggest potential mechanistic targets for stabilizing bacterial cells under low-water-activity conditions.

Within lignocellulosic biomass, xylose is the second most abundant sugar after glucose. As a renewable and sustainable substrate, it is gaining attention as a feedstock for microbial bioprocesses. In this study, we demonstrated the co-production of polyhydroxybutyrate (PHB) and violacein from xylose. We initially confirmed the feasibility of co-production through genome-scale metabolic simulations, followed by optimization using a hybrid expression system that combines a conventional tac promoter and synthetic promoter-ribosome-binding site-terminator (semi-endo PRT) elements in dual plasmids. Additionally, we assessed the antimicrobial activity of violacein against type I methanotrophs. Recombinant Escherichia coli DH5α harboring a hybrid system produced 111.3 ± 19.7 and 0.88 ± 0.23 mg/L of PHB and violacein, respectively, in M9 using xylose as the sole carbon source, without tryptophan supplementation. Using the synthetic PRT system, 528.9 ± 104 mg/g dry cell weight (DCW) of PHB was obtained. Additionally, violacein inhibits the growth of Methylomicrobium alcaliphilum 20Z at 9 µg/mL in nitrate mineral salt medium containing methanol as the sole carbon source. The use of lignocellulose-derived sugars for co-production offers an environmentally sustainable bio-manufacturing approach that contributes to greenhouse gas mitigation and supports the transition toward a circular bioeconomy.

BackgroundAccurate cellular models are critical for understanding tissue function and accelerating drug discovery. While in vitro systems like spheroids and organoids are widely used, they are costly, low-throughput, and often lack reproducibility. Here, we introduce Evolvoid, a computational pipeline based on genetic algorithms that generates virtual 3D spheroid-like cell constructs with optimized morphologies by simulating key biophysical principles — such as thermodynamic principles, nutrient transport and their uptake by cells.ResultsBy integrating finite element simulations with evolutionary principles, our in silico platform evolves populations of randomly generated shapes, iteratively selecting individuals that best satisfy a biophysically informed fitness function. The fitness function encodes selection pressures based on general biophysical constraints — namely, the minimization of surface energy and the maintenance of cell viability under variable oxygen conditions. The Shannon entropy is used to track genome complexity over generations. In consistence with evolutionary dynamics, the complexity increases progressively. Moreover, albeit based on basic biophysical optimization rules, the fittest individuals generated by Evolvoid closely resemble the shape and size of cellular spheroids obtained in vitro.ConclusionEvolvoid is modular, scalable, and tunable to different construct sizes, cell types, or culture conditions, and thus provides a versatile platform for designing and optimizing 3D cellular models entirely in silico. It offers a foundation for developing high-fidelity, cost-effective digital shape twins of biological systems, supporting the advancement of lab-on-a-laptop technologies and new approach methodologies, thereby reducing the reliance on in vitro and animal models.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13036-026-00642-z.

In this study, the cocktail medium significantly enhanced antifungal metabolite production, thereby improving the suppression of peanut web blotch caused by Peyronellaea arachidicola. A novel antagonistic bacterial strain was isolated from cultivated peanut soil and identified as Bacillus velezensis WY-65. Additionally, the metabolomic profile of strain WY-65 was investigated under two fermentation conditions: basic fermentation medium (BFM) and cocktail fermentation medium (CFM). In vitro assays revealed that the cell-free supernatant (CFS) from WY-65 cultured in CFM inhibited P. arachidicola by 87.68%, whereas the CFS from BFM inhibited P. arachidicola by 61.42%. Greenhouse trials targeting peanut web blotch demonstrated that CFM achieved a disease control efficiency of 92%, whereas BFM exhibited a control efficiency of 86%. Treatment with CFM reduced the disease incidence to 8.71%, and BFM treatment resulted in a disease incidence of 15%. In contrast, the control group presented a disease incidence of 95%. CFS significantly impacted the efflux pump and caused ROS in P. arachidicola. Using untargeted LC‒MS/UHPLC-based metabolomics, we identified distinct metabolic signatures influenced by medium composition, revealing an enrichment of bioactive secondary metabolites, including 3-indoleacrylic acid and L-tryptophan, in CFM. KEGG differential abundance (DA) analysis revealed that strain WY-65 cultured in CFM underwent broad metabolic reprogramming, with significant enrichment in amino acid biosynthesis and the phenylalanine, tyrosine, and tryptophan synthesis pathways. Pathway topology analysis further revealed that glycine, serine, and threonine metabolism and phenylalanine, tyrosine, and tryptophan synthesis pathways had the greatest impact and significance, highlighting their central roles in stress adaptation and antimicrobial precursor biosynthesis. In vitro confirmatory tests with synthetic chemicals confirmed the bioactivity of these compounds. At 200 μL, both 3-indoleacrylic acid and L-tryptophan exhibited peak antifungal activity (91% and 89%, respectively), whereas their activities at 150 μL (87% vs. 75%) and 300 μL (89% vs. 80%) were comparatively lower. Our findings provide insight into medium-induced metabolomic modulation in strain WY-65 and highlight its potential as a robust biocontrol agent for sustainable peanut web blot disease management. Not applicable.

Chikungunya virus (CHIKV) and Dengue virus (DENV) infections present with highly similar clinical symptoms but require distinct management strategies, highlighting an urgent need for rapid and accurate differential diagnostic methods. The current gold standard, reverse transcription quantitative real-time PCR (RT-qPCR), has significant limitations: it relies on expensive thermal cyclers, complex laboratory infrastructure, and specialized personnel, making it difficult to implement in resource-limited settings and for on-site screening. To address this technological bottleneck, this study developed a portable, instrument-independent rapid detection technology based on the CRISPR-Cas12a/Cas13a dual-enzyme cleavage system. By precisely designing specific crRNAs targeting the CHIKV E1 gene and the DENV 3′-UTR region, and integrating them with reverse transcription recombinase-aided amplification (RT-RAA) technology, we established an integrated reaction system that performs nucleic acid amplification and detection under isothermal conditions. The core mechanism of the technology is as follows: upon recognition of the corresponding viral targets, Cas12a (targeting CHIKV) and Cas13a (targeting DENV) become activated and cleave fluorescent reporters or lateral flow strip reporter probes, enabling visual detection. Gradient-diluted viral nucleic acid tests indicated that the lowest detectable concentration that generated a signal reached 10² copies/mL, which is comparable to qPCR. Clinical simulated sample validation showed 100% overall agreement with qPCR, and the system accurately distinguished single infections from co-infections.The CRISPR dual-enzyme cleavage technology established in this study effectively circumvents the reliance of qPCR on sophisticated equipment, providing a rapid, simple, and low-cost solution for CHIKV/DENV differential diagnosis. It holds significant practical value for the early prevention and control of arboviral diseases.