Current opinion in biotechnology最新文献

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.

Microalgae are eukaryotic photosynthetic micro-organisms that convert CO₂ into carbohydrates, lipids, and other valuable metabolites. They are considered promising chassis for the production of various bioproducts, including fatty acid–derived biofuels. However, algae-based biofuels are not yet commercially available, mainly because of their low yields and high production cost. Optimizing strains to improve lipid productivity using the principles of synthetic biology should help move forward. This necessitates developments in the following areas: (1) identification of molecular bricks (enzymes, transcription factors, regulatory proteins etc.); (2) development of genetic tools; and (3) availability of high-throughput phenotyping methods. Here, we highlight the most recent developments in some of these areas and provide examples of the use of genome editing tools to improve oil content.

Genome editing (GE) has emerged as a technology that could revolutionize food and agricultural production. While its advent has evoked enthusiasm for a more sustainable food system, there exists heterogeneity in regulations and public opinions regarding the technology. This review discusses evidence on the implications of government regulations on GE, and perceptions of genome-edited (GEd) food and related regulations. The review highlights consumers’ positive attitude and preference for GEd foods when compared with genetically modified foods, despite the limited awareness and knowledge of GE technology. While policy changes might trigger debates, providing tailored benefits, information to consumers could further improve their attitude toward GE.

A central goal of synthetic biology is the reprogramming of living systems for predetermined biological functions. While many engineering efforts have been made in living systems, these innovations have been mainly employed with microorganisms or cell lines. The engineering of multicellular organisms including animals remains challenging owing to the complexity of these systems. In this context, microbes, with their intricate impact on animals, have opened new opportunities. Through the utilization of the symbiotic relationships between microbes and animals, researchers have effectively manipulated animals in various ways using engineered microbes. This focused approach has demonstrated its significance in scientific exploration and engineering with model animals, coral preservation and restoration, and advancements in human health.

Molecular optogenetics utilizes genetically encoded, light-responsive protein switches to control the function of molecular processes. Over the last two years, there have been notable advances in the development of novel optogenetic switches, their utilization in elucidating intricate signaling pathways, and their progress toward practical applications in biotechnological processes, material sciences, and therapeutic applications. In this review, we discuss these areas, offer insights into recent developments, and contemplate future directions.

With the continuous increment in global population growth, compounded by post-pandemic food security challenges due to labor shortages, effects of climate change, political conflicts, limited land for agriculture, and carbon emissions control, addressing food production in a sustainable manner for future generations is critical. Microorganisms are potential alternative food sources that can help close the gap in food production. For the development of more efficient and yield-enhancing products, it is necessary to have a better understanding on the underlying regulatory molecular pathways of microbial growth. Nevertheless, as microbes are regulated at multiomics scales, current research focusing on single omics (genomics, proteomics, or metabolomics) independently is inadequate for optimizing growth and product output. Here, we discuss digital twin (DT) approaches that integrate systems biology and artificial intelligence in analyzing multiomics datasets to yield a microbial replica model for in silico testing before production. DT models can thus provide a holistic understanding of microbial growth, metabolite biosynthesis mechanisms, as well as identifying crucial production bottlenecks. Our argument, therefore, is to support the development of novel DT models that can potentially revolutionize microorganism-based alternative food production efficiency.

High-throughput screening technologies have been lacking in comparison to the plethora of high-throughput genetic diversification techniques developed in biotechnology. This review explores the challenges and advancements in high-throughput screening for high-value natural products, focusing on the critical need to expand ligand targets for biosensors and increase the throughput of analytical techniques in screening microbial cell libraries for optimal strain performance. The engineering techniques to broaden the scope of ligands for biosensors, such as transcription factors, G protein–coupled receptors and riboswitches are discussed. On the other hand, integration of microfluidics with traditional analytical methods is explored, covering fluorescence-activated cell sorting, Raman-activated cell sorting and mass spectrometry, emphasising recent developments in maximising throughput.

Reprogramming cells will play a fundamental role in shaping the future of cell therapies by developing new strategies to engineer cells for improved performance and higher-order physiological functions. Approaches in synthetic biology harness cells’ natural ability to sense diverse signals, integrate environmental inputs to make decisions, and execute complex behaviors based on the health of the organism or tissue. In this review, we highlight strategies in synthetic biology to reprogram cells, and discuss how recent approaches in the delivery of modified mRNA have created new opportunities to alter cell function in vivo. Finally, we discuss how combining concepts from synthetic biology and the delivery of mRNA in vivo could provide a platform for innovation to advance in vivo cellular reprogramming.

In-depth profiling of cancer cells/tissues is expanding our understanding of the genomic, epigenomic, transcriptomic, and proteomic landscape of cancer. However, the complexity of the cancer microenvironment, particularly its immune regulation, has made it difficult to exploit the potential of cancer immunotherapy. High-throughput spatial omics technologies and analysis pipelines have emerged as powerful tools for tackling this challenge. As a result, a potential revolution in cancer diagnosis, prognosis, and treatment is on the horizon. In this review, we discuss the technological advances in spatial profiling of cancer around and beyond the central dogma to harness the full benefits of immunotherapy. We also discuss the promise and challenges of spatial data analysis and interpretation and provide an outlook for the future.