Hasil untuk "Biotechnology"

A. D. dos Santos, F. Cervantes, J. V. van Lier

F. Fukuyama

M. K. Bhat

K. Jaeger, T. Eggert

R. Speece

David L. Wheeler, D. Church, S. Federhen et al.

E. Becker

T. Kotnik, W. Frey, M. Sack et al.

J. M. Lucht

A wide gap exists between the rapid acceptance of genetically modified (GM) crops for cultivation by farmers in many countries and in the global markets for food and feed, and the often-limited acceptance by consumers. This review contrasts the advances of practical applications of agricultural biotechnology with the divergent paths—also affecting the development of virus resistant transgenic crops—of political and regulatory frameworks for GM crops and food in different parts of the world. These have also shaped the different opinions of consumers. Important factors influencing consumer’s attitudes are the perception of risks and benefits, knowledge and trust, and personal values. Recent political and societal developments show a hardening of the negative environment for agricultural biotechnology in Europe, a growing discussion—including calls for labeling of GM food—in the USA, and a careful development in China towards a possible authorization of GM rice that takes the societal discussions into account. New breeding techniques address some consumers’ concerns with transgenic crops, but it is not clear yet how consumers’ attitudes towards them will develop. Discussions about agriculture would be more productive, if they would focus less on technologies, but on common aims and underlying values.

Giulio Tesei, Francesco Pesce, Kresten Lindorff-Larsen

Protein design has the potential to revolutionize biotechnology and medicine. While most efforts have focused on proteins with well-defined structures, increased recognition of the functional significance of intrinsically disordered regions, together with improvements in their modeling, has paved the way to their computational de novo design. This review summarizes recent advances in engineering intrinsically disordered regions with tailored conformational ensembles, molecular recognition, and phase behavior. We discuss challenges in combining models with predictive accuracy with scalable design workflows and outline emerging strategies that integrate knowledge-based, physics-based, and machine-learning approaches.

Nathan S. Babcock, Brandy N. Babcock

This technical monograph provides a comprehensive overview of the field of quantum biology. It approaches quantum biology from a physical perspective with core quantum mechanical concepts presented foremost to provide a theoretical foundation for the field. An extensive body of research is covered to clarify the significance of quantum biology as a scientific field, outlining the field's long-standing importance in the historical development of quantum theory. This lays the essential groundwork to enable further advances in nanomedicine and biotechnology. Written for academics, biological science researchers, physicists, biochemists, medical technologists, and students of quantum mechanics, this text brings clarity to fundamental advances being made in the emerging science of quantum biology.

Zabin K. Bagewadi, Gouri H. Illanad, T. M. Yunus Khan et al.

Abstract The current investigation reports anti-cancer, antioxidant and antibacterial potential of L-Glutaminase (Streptomyces roseolus strain ZKB1) and L-Glutaminase capped nanoparticles. The highest L-Glutaminase production of 9.57 U/mL was achieved on the 4th day of fermentation when L-Glutamine was used as the sole carbon and nitrogen source. Enhanced recycling stability was observed after 6 cycles using L-Glutaminase immobilized in 3% agar and agarose matrices. Free and immobilized L- Glutaminase showed K m of 13.89 ± 0.8 and 7.13 ± 0.3 mM and V max of 18.40 ± 1.5 and 24.21 ± 1.7 U/mg respectively. L- Glutaminase capped silver (AgNP) and zinc oxide (ZnONP) nanoparticles were synthesized and structurally characterized using UV visible spectroscopy, FTIR, SEM–EDS, XRD and AFM. L- Glutaminase capped AgNP and ZnONP exhibited good thermal stability with five and three stages weight loss pattern respectively based on TGA. L-Glutaminase capped AgNP exhibited highest inhibitory activity against B. subtilis (45 $$\pm$$ ± 0.5 mm) and E. coli (33 $$\pm$$ ± 0.8 mm) whereas, L-Glutaminase capped ZnONP demonstrated highest inhibition against E. coli (30 $$\pm$$ ± 0.3 mm) and B. cereus (25 $$\pm$$ ± 0.5 mm). Increased nanoparticles concentration exhibited increased inhibitory potential as compared to wild L-Glutaminase and lowest MIC of 0.09 µg/mL was exhibited against B. cereus. L-Glutaminase capped nanoparticles demonstrated significant antioxidant properties through in-vitro ABTS and DPPH radical scavenging assays in a dosage-dependent manner. L-Glutaminase and capped AgNP and ZnONP, demonstrated pronounced cell cytotoxicity against MCF-7 cancerous cell line with 57.17 µg/mL, 8.13 µg/mL and 28.31 µg/mL IC50 values respectively, suggesting promising properties as anticancer agents in enzyme-based therapy. The results reveal promising biological activities with potential applications in healthcare sector. Graphical Abstract

Fatma Al‐zahraa A. Yehia, Galal Yahya, Eslam M. Elsayed et al.

ABSTRACT Enterococcus species, natural inhabitants of the human gut, have become major causes of life‐threatening bloodstream infections (BSIs) and the third most frequent cause of hospital‐acquired bacteremia. The rise of high‐level gentamicin resistance (HLGR) in enterococcal isolates complicates treatment and revives bacteriophage therapy. This study isolated and identified forty E. faecalis clinical isolates, with 30% exhibiting HLGR. The HLGR5 isolate, resistant to fosfomycin, vancomycin, and linezolid, was used to isolate the vB_EfaS_SZ1 phage from effluent water. This phage specifically lysed 42% of HLGR isolates. vB_EfaS_SZ1 demonstrated beneficial traits, including thermal stability, acid–base tolerance, a short latent period, and a large burst size. The phage genome comprises a 40,942 bp linear double‐stranded DNA with 65 open reading frames (ORFs). The genome closely resembled Enterococcus phages, classifying it within the Efquatrovirus genus. Phage‐antibiotic synergy was assessed using checkerboard assays and time‐killing analyses, revealing enhanced bacteriolytic activity of ampicillin and fosfomycin, with significant reductions in minimum inhibitory concentration values. In a mouse bacteremia model, phage‐antibiotic combinations significantly reduced E. faecalis liver burden compared to monotherapies. Histopathological analysis confirmed therapeutic synergy, showing reduced inflammation and improved hepatocyte regeneration. These findings underscore the potential of phage vB_EfaS_SZ1 as an adjunct to antibiotic therapy for resistant enterococcal bacteremia.

Rui Zhang, Rui Xin, Margo Seltzer et al.

Interpretability is crucial for doctors, hospitals, pharmaceutical companies and biotechnology corporations to analyze and make decisions for high stakes problems that involve human health. Tree-based methods have been widely adopted for survival analysis due to their appealing interpretablility and their ability to capture complex relationships. However, most existing methods to produce survival trees rely on heuristic (or greedy) algorithms, which risk producing sub-optimal models. We present a dynamic-programming-with-bounds approach that finds provably-optimal sparse survival tree models, frequently in only a few seconds.

Liguo Chen, Hongyang Hua, Xinyue Luo et al.

Ocean warming significantly affects the fishing industry, with species like Scottish herring and mackerel migrating northwards. Our research, a fusion of artificial intelligence, data science, and operations research, addresses this crisis. Using Long Short Term Memory networks, we forecast sea surface temperatures (SST) and model fish migratory patterns with Enhanced Cellular Automata. A corrective factor within our model adjusts for human impact on SST, guiding diverse mitigation scenarios. We apply operational research to strategize responses, including the modernization of fishing vessels as a less costly alternative to relocation. Our data-driven approach, suggesting fleet modernization, strategic relocation, and product diversification, offers an effective approach to mitigating the threats to the ocean warming phenomenon.

Vasiliki Bikia, Georgios Rovas, Stamatia Pagoulatou et al.

Sutha Paramasivam, Sathishkumar Chidambaram, Palanisamy Karumalaiyan et al.

<b>Background:</b> Green synthesized nanoparticles (NPs) have gained increasing popularity in recent times due to their broad spectrum of antimicrobial properties. This study aimed to develop a phytofabrication approach for producing cuprous (Cu₂O) and cupric oxide (CuO) NPs using a simple, non-hazardous process and to examine their antimicrobial properties. <b>Methods:</b> The synthesis employed <i>Bidens pilosa</i> plant extract as a natural reducing and stabilizing agent, alongside copper chloride dihydrate as the precursor. The biosynthesized NPs were characterized through various techniques, including X-ray diffraction (XRD), transmission electron microscopy (TEM), Fourier-transform infrared (FT-IR) spectroscopy, ultraviolet–visible (UV-Vis) spectroscopy, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS). <b>Results:</b> XRD analysis confirmed that the synthesized CuO and Cu₂O NPs exhibited a high degree of crystallinity, with crystal structures corresponding to monoclinic and face-centered cubic systems. SEM images revealed that the NPs displayed distinct spherical and sponge-like morphologies. EDS analysis further validated the purity of the synthesized CuO NPs. The antimicrobial activity of the CuO and Cu₂O NPs was tested against various pathogenic bacterial strains, including <i>Staphylococcus aureus</i>, <i>Pseudomonas aeruginosa</i>, <i>Escherichia coli</i>, and <i>Bacillus cereus</i>, with the minimum inhibitory concentration (MIC) used to gauge their effectiveness. <b>Conclusions:</b> The results showed that the phytosynthesized NPs had promising antibacterial properties, particularly the Cu₂O NPs, which, with a larger crystal size of 68.19 nm, demonstrated significant inhibitory effects across all tested bacterial species. These findings suggest the potential of CuO and Cu₂O NPs as effective antimicrobial agents produced via green synthesis.

Rohan Balakrishnan, Jonas Cremer

Protein synthesis is an important determinant of microbial growth and response that demands a high amount of metabolic and biosynthetic resources. Despite these costs, microbial species from different taxa and habitats massively synthesize proteins that are not utilized in the conditions they currently experience. Based on resource allocation models, recent studies have begun to reconcile the costs and benefits of these conditionally unutilized proteins (CUPs) in the context of varying environmental conditions. Such massive synthesis of CUPs is crucial to consider in different areas of modern microbiology, from the systematic investigation of cell physiology, via the prediction of evolution in laboratory and natural environments, to the rational design of strains in biotechnology applications.

Jennifer Harnett, Simon Weir, Davide Michieletto

In this paper we investigate the effects of varying cation valency and concentration on the rheology of entangled lambda DNA solutions. We show that monovalent cations moderately increase the viscoelasticty of the solutions mainly by stabilising linear condensation of lambda DNA ``monomers'' via hybridisation of their sticky ends. On the contrary, divalent cations have a far more complex and dramatic effect on the rheology of the solution and we observe evidence of inter-molecular DNA-DNA bridging by Mg2+. We argue that these results may be interesting in the context of dense solutions of single and double stranded DNA, e.g. in vivo or in biotechnology applications such as DNA origami and DNA hydrogels.

Joshua A. M. Kaste, Yair Shachar-Hill

13C-Metabolic Flux Analysis (13C-MFA) and Flux Balance Analysis (FBA) are widely used to investigate the operation of biochemical networks in both biological and biotechnological research. Both of these methods use metabolic reaction network models of metabolism operating at steady state, so that reaction rates (fluxes) and the levels of metabolic intermediates are constrained to be invariant. They provide estimated (MFA) or predicted (FBA) values of the fluxes through the network in vivo, which cannot be measured directly. A number of approaches have been taken to test the reliability of estimates and predictions from constraint-based methods and to decide on and/or discriminate between alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, validation and model selection methods have been underappreciated and underexplored. We review the history and state-of-the-art in constraint-based metabolic model validation and model selection. Applications and limitations of the X2-test of goodness-of-fit, the most widely used quantitative validation and selection approach in 13C-MFA, are discussed, and complementary and alternative forms of validation and selection are proposed. A combined model validation and selection framework for 13C-MFA incorporating metabolite pool size information that leverages new developments in the field is presented and advocated for. Finally, we discuss how the adoption of robust validation and selection procedures can enhance confidence in constraint-based modeling as a whole and ultimately facilitate more widespread use of FBA in biotechnology in particular.