Introduction
Pseudomonas aeruginosa , a Gram-negative bacterium, is the predominant organism found in hospital settings (Bassetti et al., 2018). The formation of biofilms, along with other virulence factors, in this pathogen is a quorum sensing (QS) mediated process (Moura-Alves et al., 2019). The LasI-LasR and rhlI-rhlR QS systems govern the virulence of P. aeruginosa by regulating the secretion of exotoxins and exoenzymes such as protease, alginate, and extracellular polymeric substances, which contribute to biofilm development (Moura-Alves et al., 2019). The growth of biofilms relies on QS-mediated swarming motility controlled by the rhl system and other QS systems in P. aeruginosa , which play a crucial role in infection development. Inhibition of QS systems can attenuate bacterial virulence, as they are key players in pathogenicity (Chadha et al., 2022). Consequently, numerous studies have investigated QS inhibitors and biofilm inhibitors to mitigate biofilm formation and the associated virulence factors (Aleksić et al., 2017, Gökalsın et al., 2017). Given the escalating prevalence of drug-resistant biofilms and their resistance to conventional antibiotics, there is an urgent need for natural compounds that can serve as both QS inhibitors and biofilm inhibitors.
Chitosan, a natural marine polysaccharide macromolecule, is derived from the shells of crustaceans and possesses excellent bioactive properties (Younes and Rinaudo, 2015). It is an aminopolysaccharide composed of glucosamine and n-acetyl glucosamine residues obtained through the deacetylation process of chitin found in crab and shrimp shells (Younes and Rinaudo, 2015). Due to its biodegradability, biocompatibility, and non-toxicity, chitosan has various applications and exhibits properties such as antimicrobial, immunoadjuvant, antioxidant, antitumor, antithrombogenic, and anticholesteremic effects (Yin et al., 2021). Numerous studies have confirmed its antimicrobial activity against both Gram-positive and Gram-negative bacteria, likely attributed to the interaction between positively charged chitosan molecules and negatively charged bacterial cell membranes(Kamjumphol et al., 2018, Li and Zhuang, 2020). Furthermore, chitosan has demonstrated antibiofilm activity against biofilms formed by both Gram-positive and Gram-negative bacteria (Li and Zhuang, 2020, Khan et al., 2020). However, the potential of chitosan as a QS inhibitor has not been investigated in the aforementioned studies. Additionally, understanding the efficiency of chitosan production processes is essential for enhancing quality and increasing the global economic value of chitosan.
Given the arduous and time-consuming nature of chitosan extraction methods, as well as their potential for low yields, it is imperative to optimize and establish appropriate process parameters for achieving commercial-scale chitosan production. Additionally, the demand for chitosan in numerous industrial applications has fostered interest in producing it in bulk to facilitate the availability of its raw material, derived from waste generated by the fishery industry. Process design and modeling commonly encounter a multitude of solutions, some of which may be infinite. To identify the best solution within the design region, optimization relies on effective and robust quantitative methods. Essentially, optimization involves selecting the most favorable course of action from a range of available alternatives. Response Surface Methodology (RSM) is one such optimization approach employed to establish the relationship between the dependent response variable and the independent process variables. It elucidates the synergistic and antagonistic effects exerted by these independent variables on the response. Analysis of Variance (ANOVA) further examines the significant and insignificant factors within the experimental range.
This study has two main objectives. Firstly, it aims to optimize and estimate the optimal operating conditions for producing chitosan from the white shrimp species (Metapenaeus affinis ) while modeling various responses. Secondly, it aims to investigate the anti-QS properties of extracted chitosan against Pseudomonas aeruginosa . This evaluation includes assessing its impact on P. aeruginosa’sQS-dependent phenotype, as well as the expression of QS-regulated lasR and rhlR genes, and biofilm formation.