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New Test Could Quickly Identify Bacteria That Led to Formula Shortage

Image created by Dr. Michael J. Miller

Cronobacter sakazakii
is a harmful germ that can be found in powdered baby formula. It can cause very serious health problems in infants, such as meningitis and septicemia. Right now, it takes a long time and is complicated to check if the germ is in the formula. However, a new study has created a special test that uses a computer program to find the germ in the formula. This new method makes it easier and faster to find the germ, which is known for causing serious illness in babies. It helps make sure that baby formula is safe to use.

Cronobacter sakazakii, a pathogen in powdered infant formula, poses significant risks to neonates, causing outbreaks in NICUs with high mortality rates. This Gram-negative bacterium, resistant to desiccation, can survive in dry environments like powdered formula. Despite its prevalence, current detection methods are slow, requiring skilled personnel and expensive equipment, underscoring the need for a more efficient, cost-effective solution.

In a new study published in the journal Food Quality and Safety on 22 January 2024, researchers from University of Birmingham, unveils a novel bioinformatics-based detection kit for identifying Cronobacter sakazakii in powdered infant formula. This breakthrough offers a more effective approach to detecting this harmful pathogen, commonly linked to severe infant illnesses.

In this cutting-edge study, researchers have harnessed the power of bioinformatics to create a detection kit specifically designed to identify Cronobacter sakazakii in powdered infant formula. This pathogen, known for its severe health risks to infants, has been challenging to detect with traditional methods. The research team embarked on a meticulous process, selecting genes associated with the bacterium's virulence. They then employed sophisticated immunoinformatics techniques to analyze these genes for antigenicity and epitope characteristics, leading to the creation of a multi-epitope detection kit. This bioinformatics approach allowed for the precise identification of pathogen-specific markers, making the detection kit not only innovative but also highly efficient and potentially transformative in the field of food safety.

Lead researchers Elijah K. Oladipo and Helen Onyeaka emphasize, "This study represents a major step forward in infant food safety, potentially revolutionizing how we detect and respond to foodborne pathogens like Cronobacter sakazakii."

This detection kit promises rapid and precise identification of Cronobacter sakazakii, crucial for preventing outbreaks and ensuring infant formula safety. Its application could significantly reduce the time and resources needed for pathogen detection in food safety labs. The research underscores the importance of integrating computational methods in the fight against foodborne illnesses, offering a faster, more accurate way to safeguard infant health.


Immunoinformatics Assisted Design of a Multi-Epitope Kit for Detecting Cronobacter sakazakii in Powdered Infant Formula (PIF). Oladipo,  E.K. et al. Food Quality and Safety, Published: 22 January 2024.


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, septicemia and necrotising enterocolitis among infants worldwide in association with powdered infant formula (PIF). In the present study, a peptide-based kit was designed with a bioinformatic technique to rapidly identify Cronobacter sakazakii in powdered infant formula (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 disulfide 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. 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 kilo Dalton (kDa), and a Z-score of -3.41. The multi-epitope peptide construct could be a conceptual framework for creating a Cronobacter 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.

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