Artificial intelligence-based optimization for chitosan nanoparticles biosynthesis, characterization and in‑vitro assessment of its anti-biofilm potentiality

A sustainable green-approach for biofabrication of chitosan nanoparticles, optimization, characterization, its antifungal activity against phytopathogenic Fusarium culmorum and antitumor activity

Chitosan is a natural non-toxic, biocompatible, biodegradable, and mucoadhesive polymer. It also has a broad spectrum of applications such as agriculture, medical fields, cosmetics and food industries. In this investigation, chitosan nanoparticles were produced by an aqueous extract of Cympopogon citratus leaves as a reducing agent. According to the SEM and TEM micrographs, CNPs had a spherical shape, and size ranging from 8.08 to 12.01 nm. CNPs have a positively charged surface with a Zeta potential of + 26 mV. The crystalline feature of CNPs is determined by X-ray diffraction. There are many functional groups, including C꞊C, CH2-OH, C-O, C-S, N-H, CN, CH and OH were detected by FTIR analysis. As shown by the thermogravimetric study, CNPs have a high thermal stability. For the optimization of the green synthesis of CNPs, a Face centered central composite design (FCCCD) with 30 trials was used. The maximum yield of CNPs (13.99 mg CNPs/mL) was produced with chitosan concentration 1.5%, pH 4.5 at 40 °C, and incubation period of 30 min. The antifungal activity of CNPs was evaluated against phytopathogenic fungus; Fusarium culmorum. A 100% rate of mycelial growth inhibition was gained by the application of 20 mg CNPs/mL. The antitumor activity of the green synthesized CNPs was examined using 6 different cell lines, the viability of the cells reduced when the concentration of green synthesized CNPs increased, the IC50 dose of the green synthesized CNPs on the examined cell lines HePG-2, MCF-7, HCT-116, PC-3, Hela and WI-38 was 36.25 ± 2.3, 31.21 ± 2.2, 67.45 ± 3.5, 56.30 ± 3.3, 44.62 ± 2.6 and 74.90 ± 3.8; respectively.

Bionanofactory for green synthesis of collagen nanoparticles, characterization, optimization, in-vitro and in-vivo anticancer activities

Collagen nanoparticles (collagen-NPs) are promising biological polymer nanoparticles due to their exceptional biodegradability and biocompatibility. Collagen-NPs were bio-fabricated from pure marine collagen using the cell-free supernatant of a newly isolated strain, Streptomyces sp. strain NEAA-3. Streptomyces sp. strain NEAA-3 was identified as Streptomyces plicatus strain NEAA-3 based on its cultural, morphological, physiological properties and 16S rRNA sequence analysis. The sequence data has been deposited under accession number OR501412.1 in the GenBank database. The face-centered central composite design (FCCD) was used to improve collagen-NPs biosynthesis. The maximum yield of collagen-NPs was 9.33 mg/mL with a collagen concentration of 10 mg/mL, an initial pH of 7, an incubation time of 72 h, and a temperature of 35 °C. Using the desirability function approach, the collagen-NPs biosynthesis obtained after FCCD optimization (9.53 mg/mL) was 3.92 times more than the collagen-NPs biosynthesis obtained before optimization process (2.43 mg/mL). The TEM analysis of collagen-NPs revealed hollow sphere nanoscale particles with an average diameter of 33.15 ± 10.02 nm. FTIR spectra confirmed the functional groups of the collagen, collagen-NPs and the cell-free supernatant that are essential for the efficient capping of collagen-NPs. The biosynthesized collagen-NPs exhibited antioxidant activity and anticancer activity against HeP-G2, MCF-7 and HCT116 cell lines. Collagen-NPs assessed as an effective drug loading carrier with methotrexate (MTX), a chemotherapeutic agent. The TEM analysis revealed that the average size of MTX-loaded collagen-NPs was 35.4 ± 8.9 nm. The percentages of drug loading (DL%) and encapsulation efficiency (EE%) were respectively 22.67 and 45.81%.

Process optimization for gold nanoparticles biosynthesis by Streptomyces albogriseolus using artificial neural network, characterization and antitumor activities

Gold nanoparticles (GNPs) are highly promising in cancer therapy, wound healing, drug delivery, biosensing, and biomedical imaging. Furthermore, GNPs have anti-inflammatory, anti-angiogenic, antioxidants, anti-proliferative and anti-diabetic effects. The present study presents an eco-friendly approach for GNPs biosynthesis using the cell-free supernatant of Streptomyces albogriseolus as a reducing and stabilizing agent. The biosynthesized GNPs have a maximum absorption peak at 540 nm. The TEM images showed that GNPs ranged in size from 5.42 to 13.34 nm and had a spherical shape. GNPs have a negatively charged surface with a Zeta potential of - 24.8 mV. FTIR analysis identified several functional groups including C-H, -OH, C-N, amines and amide groups. The crystalline structure of GNPs was verified by X-ray diffraction and the well-defined and distinct diffraction rings observed by the selected area electron diffraction analysis. To optimize the biosynthesis of GNPs using the cell-free supernatant of S. albogriseolus, 30 experimental runs were conducted using central composite design (CCD). The artificial neural network (ANN) was employed to analyze, validate, and predict GNPs biosynthesis compared to CCD. The maximum experimental yield of GNPs (778.74 μg/mL) was obtained with a cell-free supernatant concentration of 70%, a HAuCl4 concentration of 800 μg/mL, an initial pH of 7, and a 96-h incubation time. The theoretically predicted yields of GNPs by CCD and ANN were 809.89 and 777.32 μg/mL, respectively, which indicates that ANN has stronger prediction potential compared to the CCD. The anticancer activity of GNPs was compared to that of doxorubicin (Dox) in vitro against the HeP-G2 human cancer cell line. The IC50 values of Dox and GNPs-based treatments were 7.26 ± 0.4 and 22.13 ± 1.3 µg/mL, respectively. Interestingly, treatments combining Dox and GNPs together showed an IC50 value of 3.52 ± 0.1 µg/mL, indicating that they targeted cancer cells more efficiently.

A bibliometric analysis on discovering anti-quorum sensing agents against clinically relevant pathogens: current status, development, and future directions

Background

Quorum sensing is bacteria's ability to communicate and regulate their behavior based on population density. Anti-quorum sensing agents (anti-QSA) is promising strategy to treat resistant infections, as well as reduce selective pressure that leads to antibiotic resistance of clinically relevant pathogens. This study analyzes the output, hotspots, and trends of research in the field of anti-QSA against clinically relevant pathogens.

Methods

The literature on anti-QSA from the Web of Science Core Collection database was retrieved and analyzed. Tools such as CiteSpace and Alluvial Generator were used to visualize and interpret the data.

Results

From 1998 to 2023, the number of publications related to anti-QAS research increased rapidly, with a total of 1,743 articles and reviews published in 558 journals. The United States was the largest contributor and the most influential country, with an H-index of 88, higher than other countries. Williams was the most productive author, and Hoiby N was the most cited author. Frontiers in Microbiology was the most prolific and the most cited journal. Burst detection indicated that the main frontier disciplines shifted from MICROBIOLOGY, CLINICAL, MOLECULAR BIOLOGY, and other biomedicine-related fields to FOOD, MATERIALS, NATURAL PRODUCTS, and MULTIDISCIPLINARY. In the whole research history, the strongest burst keyword was cystic-fibrosis patients, and the strongest burst reference was Lee and Zhang (2015). In the latest period (burst until 2023), the strongest burst keyword was silver nanoparticle, and the strongest burst reference was Whiteley et al. (2017). The co-citation network revealed that the most important interest and research direction was anti-biofilm/anti-virulence drug development, and timeline analysis suggested that this direction is also the most active. The key concepts alluvial flow visualization revealed seven terms with the longest time span and lasting until now, namely Escherichia coli, virulence, Pseudomonas aeruginosa, virulence factor, bacterial biofilm, gene expression, quorum sensing. Comprehensive analysis shows that nanomaterials, marine natural products, and artificial intelligence (AI) may become hotspots in the future.

Conclusion

This bibliometric study reveals the current status and trends of anti-QSA research and may assist researchers in identifying hot topics and exploring new research directions.

Advancing understanding of microbial biofilms through machine learning-powered studies

Microbial biofilms are prevalent in various environments and pose significant challenges to food safety and public health. The biofilms formed by pathogens can cause food spoilage, foodborne illness, and infectious diseases, which are difficult to treat due to their enhanced antimicrobial resistance. While the composition and development of biofilms have been widely studied, their profound impact on food, the food industry, and public health has not been sufficiently recapitulated. This review aims to provide a comprehensive overview of microbial biofilms in the food industry and their implication on public health. It highlights the existence of biofilms along the food-producing chains and the underlying mechanisms of biofilm-associated diseases. Furthermore, this review thoroughly summarizes the enhanced understanding of microbial biofilms achieved through machine learning approaches in biofilm research. By consolidating existing knowledge, this review intends to facilitate developing effective strategies to combat biofilm-associated infections in both the food industry and public health.

Green fabrication of chitosan nanoparticles using Lavendula angustifolia, optimization, characterization and in‑vitro antibiofilm activity

Chitosan nanoparticles (CNPs) are promising polymeric nanoparticles with exceptional physicochemical, antimicrobial and biological characteristics. The CNPs are preferred for a wide range of applications in the food industry, cosmetics, agriculture, medical, and pharmaceutical fields due to their biocompatibility, biodegradability, eco-friendliness, and non-toxicity. In the current study, a biologically based approach was used to biofabricate CNPs using an aqueous extract of Lavendula angustifolia leaves as a reducing agent. The TEM images show that the CNPs were spherical in shape and ranged in size from 7.24 to 9.77 nm. FTIR analysis revealed the presence of several functional groups, including C-H, C-O, CONH₂, NH₂, C-OH and C-O-C. The crystalline nature of CNPs is demonstrated by X-ray diffraction. The thermogravimetric analysis revealed that CNPs are thermally stable. The CNPs' surface is positively charged and has a Zeta potential of 10 mV. For optimising CNPs biofabrication, a face-centered central composite design (FCCCD) with 50 experiments was used. The artificial intelligence-based approach was used to analyse, validate, and predict CNPs biofabrication. The optimal conditions for maximum CNPs biofabrication were theoretically determined using the desirability function and experimentally verified. The optimal conditions that maximize CNPs biofabrication (10.11 mg/mL) were determined to be chitosan concentration 0.5%, leaves extract 75%, and initial pH 4.24. The antibiofilm activity of CNPs was evaluated in‑vitro. The results show that 1500 μg/mL of CNPs suppressed P. aeruginosa, S. aureus and C. albicans biofilm formation by 91.83 ± 1.71%, 55.47 ± 2.12% and 66.4 ± 1.76%; respectively. The promising results of the current study in biofilm inhibition by necrotizing biofilm architecture, reducing its significant constituents and inhibiting microbial cell proliferation encourage their use as natural biosafe and biocompatible anti-adherent coating in antibiofouling membranes, medical bandage/tissues and food packaging materials.