Current opinion in biotechnology最新文献

Transgenic approaches are now standard in plant biology research aiming to characterize gene function or improve crops. Recent advances in DNA synthesis and assembly make constructing transgenes a routine task. What remains nontrivial is the selection of the DNA parts and optimization of the transgene design. Early career researchers and seasoned molecular biologists alike often face difficult decisions on what promoter or terminator to use, what tag to include, and where to place it. This review aims to inform about the current approaches being employed to identify and characterize DNA parts with the desired functionalities and give general advice on basic construct design. Furthermore, we hope to share the excitement about new experimental and computational tools being developed in this field.

Although plants are sessile, their ubiquitous distribution, ability to harness energy from the sun, and ability to sense above and belowground signals make them ideal candidates for biosensor development. Synthetic biology has allowed scientists to reimagine biosensors as engineered devices that are focused on accomplishing novel tasks. As such, a new wave of plant-based sensors, phytosensors, are being engineered as multi-component sense-and-report devices that can alert human operators to a variety of hazards. While phytosensors are intrinsically tied to agriculture, a new generation of phytosensors has been envisioned to function in the built environment and even in austere environments, such as space. In this review, we will explore the current state of the art with regard to phytosensor engineering.

Plant natural products (PNPs) are a diverse group of chemical compounds synthesized by plants for various biological purposes and play a significant role in the fields of medicine, agriculture, and industry. In recent years, the development of synthetic biology promises the production of PNPs in microbial expression systems in a sustainable, low-cost, and large-scale manner. This review first introduces multiplex genome editing and PNP pathway assembly in microbial expression systems. Then recent technologies and examples geared toward improving PNP biosynthetic efficiency are discussed from three aspects: pathway optimization, chassis optimization, and modular coculture engineering. Finally, the review is concluded with future perspectives on the combination of machine learning and BioFoundry for the reconstitution and optimization of PNP microbial cell factories.

Fat-soluble antioxidants play a vital role in protecting the body against oxidative stress and damage. The rapid advancements in metabolic engineering and synthetic biology have offered a promising avenue for economically producing fat-soluble antioxidants by engineering microbial chassis. This review provides an overview of the recent progress in engineering yeast microbial factories to produce three main groups of lipophilic antioxidants: carotenoids, vitamin E, and stilbenoids. In addition to discussing the classic strategies employed to improve precursor availability and alleviate carbon flux competition, this review delves deeper into the innovative approaches focusing on enzyme engineering, product sequestration, subcellular compartmentalization, multistage fermentation, and morphology engineering. We conclude the review by highlighting the prospects of microbial engineering for lipophilic antioxidant production.

Plant synthetic biology (Plant SynBio) is an emerging field with the potential to enhance agriculture, human health, and sustainability. Integrating genetic tools and engineering principles, Plant SynBio aims to manipulate cellular functions and construct novel biochemical pathways to develop plants with new phenotypic traits, enhanced yield, and be able to produce natural products and pharmaceuticals. This review compiles research efforts in reprogramming plant developmental and biochemical pathways. We highlight studies leveraging new gene expression toolkits to alter plant architecture for improved performance in model and crop systems and to produce useful metabolites in plant tissues. Furthermore, we provide insights into the challenges and opportunities associated with the adoption of Plant SynBio in addressing complex issues impacting agriculture and human health.

In the post-Green Revolution era, disparities in dietary access, rising obesity rates, demographic shifts, adoption of plant-based diets, and the impact of climate change collectively contribute to a progressive decline in dietary nutritional value, exacerbating B vitamin deficiencies across both low- and high-income countries. While the prevailing focus of biofortification has been on three micronutrients — provitamin A, iron, and zinc — utilizing conventional breeding, it is imperative to diversify biofortification strategies to combat micronutrient malnutrition. Metabolic engineering, facilitated by biotechnological tools, presents a promising avenue, contingent upon advances in fundamental knowledge, technological innovation, regulatory updates, and sustained public funding. Recognizing the intricate metabolic interplay of B vitamins in plants and humans, a comprehensive ‘from metabolism to metabolism’ approach is crucial for designing effective biofortification strategies that target multiple vitamins. This holistic perspective also extends beyond individual crops to encompass the entire food chain, a complex socioeconomic ecosystem that necessitates a paradigm shift, prioritizing quality over quantity.

Plant natural products (PNPs) play important roles in plant physiology and have been applied across diverse fields of human society. Understanding their biosynthetic pathways informs plant evolution and meanwhile enables sustainable production through metabolic engineering. However, the discovery of PNP biosynthetic pathways remains challenging due to the diversity of enzymes involved and limitations in traditional gene mining approaches. In this review, we will summarize state-of-the-art strategies and recent examples for predicting and characterizing PNP biosynthetic pathways, respectively, with multiomics-guided tools and heterologous host systems and share our perspectives on the systematic pipelines integrating these various bioinformatic and biochemical approaches.

Microbial fermentation employs two strategies: growth- and nongrowth-coupled productions. Stoichiometric metabolic models with flux balance analysis enable pathway engineering to couple target synthesis with growth, yielding numerous successful results. Growth-coupled engineering also contributes to improving bottleneck flux through subsequent adaptive evolution. However, because growth-coupled production inevitably shares resources between biomass and target syntheses, the cost-effective production of bulk chemicals mandates a nongrowth-coupled approach. In such processes, understanding how and when to transition the metabolic state from growth to production modes becomes crucial, as does maintaining cellular activity during the nongrowing state to achieve high productivity. In this paper, we review recent technologies for growth-coupled and nongrowth-coupled production, considering their advantages and disadvantages.

Glial cells are important in maintaining homeostasis for neurons in the central nervous system (CNS). During CNS disease or after injury, glia react to altered microenvironments and often acquire altered functions that contribute to disease pathology. A major focus for research is utilizing stem cell (SC)-derived glia as a potential renewable source for cell replacement to restore function, including neuronal support, and as a model for disease states to identify therapeutic targets. In this review, we focus on SC differentiation protocols for deriving three types of glial cells, astrocytes, oligodendrocytes, and microglia. These SC-derived glia can be used to identify critical cues that contribute to CNS disease progression and aid in investigation of therapeutic targets.

Classical Coulombic interaction, characterized by electrostatic interactions mediated through surface charges, is often regarded as the primary determinant in nanoparticles' (NPs) cellular association and internalization. However, the intricate physicochemical properties of particle surfaces, biomolecular coronas, and cell surfaces defy this oversimplified perspective. Moreover, the nanometrological techniques employed to characterize NPs in complex physiological fluids often exhibit limited accuracy and reproducibility. A more comprehensive understanding of nanoparticle–cell membrane interactions, extending beyond attractive forces between oppositely charged surfaces, necessitates the establishment of databases through rigorous physical, chemical, and biological characterization supported by nanoscale analytics. Additionally, computational approaches, such as in silico modeling and machine learning, play a crucial role in unraveling the complexities of these interactions.