Immunoinformatics assisted design of a multi-epitope kit for detecting Cronobacter sakazakii in powdered infant formula

Objectives Cronobacter sakazakii, formerly Enterobacter sakazakii, is an emerging ubiquitous and opportunistic foodborne pathogen with a high mortality rate. It has been implicated in cases of meningitis, septicaemia, and necrotizing enterocolitis among infants worldwide in association with powdered infant formula (PIF). This study was an insilico designed peptide base kit framework, using immunoinformatic techniques for quick detection of C. sakazakii in PIF.Materials and Methods In the present study, a peptide-based kit was designed with a bioinformatic technique to rapidly identify C. sakazakii in PIF using flhE, secY, and bcsC, which are genes responsible for its biofilm formation, as target genes. The antigenicity, membrane topology, and the presence of signal peptides of the target genes were analysed using VaxiJen, DeepTMHMM, and SignalP servers. To provide stability and flexibility to the multiple-epitope construct, the linear B cells and helper T cells (IL-4 (interleukin 4) and IL-10 (interleukin 10) inducing epitopes) were linked with a GSGSG linker followed by the addition of protein disulphide bonds. To ascertain specificity, the multi-epitope construct was molecularly docked against genes from sources other than PIF, like alfalfa, and the environment, with PIF being the highest: -328.48. Finally, the codons were modified using the pET28a(+) vector, and the resultant multi-epitope construct was successfully cloned in silico.Results The final construct had a length of 486 bp, an instability index of 23.26, a theoretical pI of 9.34, a molecular weight of 16.5 kDa, and a Z-score of -3.41.Conclusions The multi-epitope peptide construct could be a conceptual framework for creating a C. sakazakii peptide-based detection kit, which has the potential to provide fast and efficient detection. However, there is a need for additional validation through the in vitro and in vivo techniques.