Innovative biosynthesis, artificial intelligence-based optimization, and characterization of chitosan nanoparticles by Streptomyces microflavus and their inhibitory potential against Pectobacterium carotovorum

Abstract

Microbial-based strategy in nanotechnology offers economic, eco-friendly, and biosafety advantages over traditional chemical and physical protocols. The current study describes a novel biosynthesis protocol for chitosan nanoparticles (CNPs), employing a pioneer Streptomyces sp. strain NEAE-83, which exhibited a significant potential for CNPs biosynthesis. It was identified as Streptomyces microflavus strain NEAE-83 based on morphological, and physiological properties as well as the 16S rRNA sequence (GenBank accession number: MG384964). CNPs were characterized by SEM, TEM, EDXS, zeta potential, FTIR, XRD, TGA, and DSC. CNPs biosynthesis was maximized using a mathematical model, face-centered central composite design (CCFCD). The highest yield of CNPs (9.41 mg/mL) was obtained in run no. 27, using an initial pH of 5.5, 1% chitosan, 40 °C, and a 12 h incubation period. Innovatively, the artificial neural network (ANN), was used for validating and predicting CNPs biosynthesis based on the trials data of CCFCD. Despite the high precision degree of both models, ANN was supreme in the prediction of CNPs biosynthesis compared to CCFCD. ANN had a higher prediction efficacy and, lower error values (RMSE, MDA, and SSE). CNPs biosynthesized by Streptomyces microflavus strain NEAE-83 showed in-vitro antibacterial activity against Pectobacterium carotovorum, which causes the potato soft rot. These results suggested its potential application for controlling the destructive potato soft rot diseases. This is the first report on the biosynthesis of CNPs using a newly isolated; Streptomyces microflavus strain NEAE-83 as an eco-friendly approach and optimization of the biosynthesis process by artificial intelligence.

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

“…The green biosynthesis of CNPs offers many advantages, including being a one-step procedure, environmentally benign, non-toxic, and requiring less energy. Additionally, the biosynthesized CNPs are more stable 6 . The green biosynthesis of CNPs was accomplished with the help of microorganisms such as actinomycetes 6 , and fungi 43 .…”

“…Additionally, the biosynthesized CNPs are more stable 6 . The green biosynthesis of CNPs was accomplished with the help of microorganisms such as actinomycetes 6 , and fungi 43 . In addition, secondary metabolites present in aqueous extracts of plant leaves were applied as a reducing agent in the biosynthesis of nanoparticles 32,44 .…”

“…The smaller particle size of CNPs also enhances drug delivery and thus efficacy, since it is easier to transport through biological membranes 51 . Energy-dispersive X-ray spectroscopy (EDX) was applied to study the purity and to determine the structure of the sample 6 . Figure 3C shows EDX spectrum of the biosynthesized chitosan nanoparticles sample.…”

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

“…8 , was employed. The desirability function of the software Design Expert can be configured for any value between 0 (undesirable) and 1 (desirable) 22 . The desirability function's value is typically calculated theoretically before the optimization procedure is experimentally verified.…”

“…are commonly employed in the synthesis of NPs due to their capacity to produce diverse bioactive secondary metabolites and extracellular enzymes 15 – 19 . Additionally, algal pigments 1 , 2 , algal derived soluble polysaccharides 20 , fungi 21 and plant leaves extracts 22 – 24 were used for the biosynthesis of NPs due to their favorable impact on both the synthesis process and the final NPs characteristics. Microbial metabolites and phytochemicals can act as bio-reducers and/ or stabilizing/capping agents in the biosynthesis process 14 , 23 .…”