Critical Reviews in Biotechnology最新文献

Developing proteins with increased chemical space by expanding the amino acids alphabet has been an emerging technique to compete for the obstacle encountered by their need in various applications. 3,4-Dihydroxyphenylalanine (L-DOPA) catecholic unnatural amino acid is abundantly present in mussels foot proteins through post-translational modification of tyrosine to give a strong adhesion toward wet rocks. L-DOPA forms: bidentate coordination, H-bonding, metal-ligand complexes, long-ranged electrostatic, and van der Waals interactions via a pair of donor hydroxyl groups. Incorporating catechol in proteins through genetic code expansion paved the way for developing: protein-based bio-sensor, implant coating, bio-conjugation, adhesive bio-materials, biocatalyst, metal interaction and nano-biotechnological applications. The increased chemical spaces boost the protein properties by offering a new chemically active interaction ability to the protein. Here, we review the technique employed to develop a genetically expanded organism with catechol to provide novel properties and functionalities; and we highlight the importance of L-DOPA incorporated proteins in biomedical and industrial fields.

Buckwheat (Fagopyrum spp.) is a typical pseudocereal, valued for its extensive nutraceutical potential as well as its centuries-old cultivation. Tartary buckwheat and common buckwheat have been used globally and become well-known nutritious foods due to their high quantities of: proteins, flavonoids, and minerals. Moreover, its increasing demand makes it critical to improve nutraceutical, traits and yield. In this review, bioactive compounds accumulated in buckwheat were comprehensively evaluated according to their chemical structure, properties, and physiological function. Biosynthetic pathways of flavonoids, phenolic acids, and fagopyrin were methodically summarized, with the regulation of flavonoid biosynthesis. Although there are classic synthesis pathways presented in the previous research, the metabolic flow of how these certain compounds are being synthesized in buckwheat still remains uncovered. The functional genes involved in the biosynthesis of flavonols, stress response, and plant development were identified based on multi-omics research. Furthermore, it delves into the applications of multi-omics in improving buckwheat's agronomic traits, including: yield, nutritional content, stress resilience, and bioactive compounds biosynthesis. While pangenomics combined with other omics to mine elite genes, the regulatory network and mechanism of specific agronomic traits and biosynthetic of bioactive components, and developing a more efficient genetic transformation system for genetic engineering require further investigation for the execution of breeding designs aimed at enhancing desirable traits in buckwheat. This critical review will provide a comprehensive understanding of multi-omics for nutraceutical enhancement and traits improvement in buckwheat.

With antibiotic resistance on the rise, there is an urgent need for new antibacterial drugs and products to treat or prevent infection. Many such products in current use, for example human and veterinary antibiotics and antimicrobial food preservatives, were discovered and developed from nature. Natural selection acts on all living organisms and the presence of bacterial competitors or pathogens in an environment can favor the evolution of antibacterial adaptations. In this review, we ask if vultures, blow flies and other carrion users might be a good starting point for antibacterial discovery based on the selection pressure they are under from bacterial disease. Dietary details are catalogued for over 600 of these species, bacterial pathogens associated with the diets are described, and an overview of the antibacterial defenses contributing to disease protection is given. Biotechnological applications for these defenses are then discussed, together with challenges facing developers and possible solutions. Examples include use of (a) the antimicrobial peptide (AMP) gene sarcotoxin IA to improve crop resistance to bacterial disease, (b) peptide antibiotics such as serrawettin W2 as antibacterial drug leads, (c) lectins for targeted drug delivery, (d) bioconversion-generated chitin as an antibacterial biomaterial, (e) bacteriocins as antibacterial food preservatives and (f) mutualistic microbiota bacteria as alternatives to antibiotics in animal feed. We show that carrion users encounter a diverse range of bacterial pathogens through their diets and interactions, have evolved many antibacterial defenses, and are a promising source of genes, molecules, and microbes for medical, agricultural, and food industry product development.

The ornithine-urea cycle (OUC) in fungal cells has biotechnological importance and many physiological functions and is closely related to the acetyl glutamate cycle (AGC). Fumarate can be released from argininosuccinate under the catalysis of argininosuccinate lyase in OUC which is regulated by the Ca²⁺ signaling pathway and over 93.9 ± 0.8 g/L fumarate can be yielded by the engineered strain of Aureobasidium pullulans var. aubasidani in the presence of CaCO₃. Furthermore, 2.1 ± 0.02 mg of L-ornithine (L-Orn)/mg of the protein also can be synthesized via OUC by the engineered strains of Aureobasidum melanogenum. Fumarate can be transformed into many drugs and amino acids and L-Orn can be converted into siderophores (1.7 g/L), putrescine (33.4 g/L) and L-piperazic acid (L-Piz) (3.0 g/L), by different recombinant strains of A. melanogenum. All the fumarate, L-Orn, siderophore, putrescine and L-Piz have many applications. As the yeast-like fungi and the promising chassis, Aureobasidium spp, have many advantages over any other fungal strains. Further genetic manipulation and bioengineering will enhance the biosynthesis of fumarate and L-Orn and their derivates.

Even after the centenary celebration of insulin discovery, there prevail challenges concerning insulin aggregation, not only after repeated administration but also during industrial production, storage, transport, and delivery, significantly impacting protein quality, efficacy, and effectiveness. The aggregation reduces insulin bioavailability, increasing the risk of heightened immunogenicity, posing a threat to patient health, and creating a dent in the golden success story of insulin therapy. Insulin experiences various physicochemical and mechanical stresses due to modulations in pH, temperature, ionic strength, agitation, shear, and surface chemistry, during the upstream and downstream bioprocessing, resulting in insulin unfolding and subsequent fibrillation. This has fueled research in the pharmaceutical industry and academia to unveil the mechanistic insights of insulin aggregation in an attempt to devise rational strategies to regulate this unwanted phenomenon. The present review briefly describes the impacts of environmental factors of bioprocessing on the stability of insulin and correlates with various intermolecular interactions, particularly hydrophobic and electrostatic forces. The aggregation-prone regions of insulin are identified and interrelated with biophysical changes during stress conditions. The quest for novel additives, surface-active agents, and bioderived peptides in decelerating insulin aggregation, which results in overall structural stability, is described. We hope this review will help tackle the real-world challenges of insulin aggregation encountered during bioprocessing, ensuring safer, stable, and globally accessible insulin for efficient management of diabetes.

Microbes have been extensively utilized for their sustainable and scalable properties in synthesizing desired bio-products. However, insufficient knowledge about intracellular metabolism has impeded further microbial applications. The genome-scale metabolic models (GEMs) play a pivotal role in facilitating a global understanding of cellular metabolic mechanisms. These models enable rational modification by exploring metabolic pathways and predicting potential targets in microorganisms, enabling precise cell regulation without experimental costs. Nonetheless, simplified GEM only considers genome information and network stoichiometry while neglecting other important bio-information, such as enzyme functions, thermodynamic properties, and kinetic parameters. Consequently, uncertainties persist particularly when predicting microbial behaviors in complex and fluctuant systems. The advent of the omics era with its massive quantification of genes, proteins, and metabolites under various conditions has led to the flourishing of multi-constrained models and updated algorithms with improved predicting power and broadened dimension. Meanwhile, machine learning (ML) has demonstrated exceptional analytical and predictive capacities when applied to training sets of biological big data. Incorporating the discriminant strength of ML with GEM facilitates mechanistic modeling efficiency and improves predictive accuracy. This paper provides an overview of research innovations in the GEM, including multi-constrained modeling, analytical approaches, and the latest applications of ML, which may contribute comprehensive knowledge toward genetic refinement, strain development, and yield enhancement for a broad range of biomolecules.

Yeast has been established as a versatile platform for expressing functional molecules, owing to its well-characterized biology and extensive genetic modification tools. Compared to prokaryotic systems, yeast possesses advanced cellular mechanisms that ensure accurate protein folding and post-translational modifications. These capabilities are particularly advantageous for the expression of human-derived functional proteins. However, designing yeast strains as an expression platform for proteins requires the integration of molecular and cellular functions. By delving into the complexities of yeast-based expression systems, this review aims to empower researchers with the knowledge to fully exploit yeast as a functional platform to produce a diverse range of proteins. This review includes an exploration of the host strains, gene cassette structures, as well as considerations for maximizing the efficiency of the expression system. Through this in-depth analysis, the review anticipates stimulating further innovation in the field of yeast biotechnology and protein engineering.

Wastewater is a complex, but an ideal, matrix for disease monitoring and surveillance as it represents the entire load of enteric pathogens from a local catchment area. It captures both clinical and community disease burdens. Global interest in wastewater surveillance has been growing rapidly for infectious diseases monitoring and for providing an early warning of potential outbreaks. Although molecular detection methods show high sensitivity and specificity in pathogen monitoring from wastewater, they are strongly limited by challenges, including expensive laboratory settings and prolonged sample processing and analysis. Alternatively, biosensors exhibit a wide range of practical utility in real-time monitoring of biological and chemical markers. However, field deployment of biosensors is primarily challenged by prolonged sample processing and pathogen concentration steps due to complex wastewater matrices. This review summarizes the role of wastewater surveillance and provides an overview of infectious viral and bacterial pathogens with cutting-edge technologies for their detection. It emphasizes the practical utility of biosensors in pathogen monitoring and the major bottlenecks for wastewater surveillance of pathogens, and overcoming approaches to field deployment of biosensors for real-time pathogen detection. Furthermore, the promising potential of novel machine learning algorithms to resolve uncertainties in wastewater data is discussed.

Oxygenic photosynthesis in microalgae and cyanobacteria is considered an important chassis to accelerate energy transition and mitigate global warming. Currently, cultivation systems for photosynthetic microbes for large-scale applications encountered excessive light exposure stress. High light stress can: affect photosynthetic efficiency, reduce productivity, limit cell growth, and even cause cell death. Deciphering photoprotection mechanisms and constructing high-light tolerant chassis have been recent research focuses. In this review, we first briefly introduce the self-protection mechanisms of common microalgae and cyanobacteria in response to high light stress. These mechanisms mainly include: avoiding excess light absorption, dissipating excess excitation energy, quenching excessive high-energy electrons, ROS detoxification, and PSII repair. We focus on the species-specific differences in these mechanisms as well as recent advancements. Then, we review engineering strategies for creating high-light tolerant chassis, such as: reducing the size of the light-harvesting antenna, optimizing non-photochemical quenching, optimizing photosynthetic electron transport, and enhancing PSII repair. Finally, we propose a comprehensive exploration of mechanisms: underlying identified high light tolerant chassis, identification of new genes pertinent to high light tolerance using innovative methodologies, harnessing CRISPR systems and artificial intelligence for chassis engineering modification, and introducing plant photoprotection mechanisms as future research directions.

Increasing industrialization and urbanization have contributed to a significant rise in wastewater discharge and exerted extensive pressure on the existing natural energy resources. Microbial fuel cell (MFC) is a sustainable technology that utilizes wastewater for electricity generation. MFC comprises a bioelectrochemical system employing electroactive biofilms of several aerobic and anaerobic bacteria, such as Geobacter sulfurreducens, Shewanella oneidensis, Pseudomonas aeruginosa, and Ochrobacterum pseudiintermedium. Since the electroactive biofilms constitute a vital part of the MFC, it is crucial to understand the biofilm-mediated pollutant metabolism and electron transfer mechanisms. Engineering electroactive biofilm communities for improved biofilm formation and extracellular polymeric substances (EPS) secretion can positively impact the bioelectrochemical system and improve fuel cell performance. This review article summarizes the role of electroactive bacterial communities in MFC for wastewater treatment and bioelectricity generation. A significant focus has been laid on understanding the composition, structure, and function of electroactive biofilms in MFC. Various electron transport mechanisms, including direct electron transfer (DET), indirect electron transfer (IET), and long-distance electron transfer (LDET), have been discussed. A detailed summary of the optimization of process parameters and genetic engineering strategies for improving the performance of MFC has been provided. Lastly, the applications of MFC for wastewater treatment, bioelectricity generation, and biosensor development have been reviewed.