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.