Differences in Regulatory Mechanisms Induced by β-Lactoglobulin and κ-Casein in Cow's Milk Allergy Mouse Model-In Vivo and Ex Vivo Studies.
Dagmara ZłotkowskaEmilia StachurskaEwa FucBarbara WróblewskaAnita MikołajczykEwa WasilewskaPublished in: Nutrients (2021)
The presence of various proteins, including modified ones, in food which exhibit diverse immunogenic and sensitizing properties increases the difficulty of predicting host immune responses. Still, there is a lack of sufficiently reliable and comparable data and research models describing allergens in dietary matrices. The aim of the study was to estimate the immunomodulatory effects of β-lactoglobulin (β-lg) in comparison to those elicited by κ-casein (κ-CN), in vivo and ex vivo, using naïve splenocytes and a mouse sensitization model. Our results revealed that the humoral and cellular responses triggered by β-lg and κ-CN were of diverse magnitudes and showed different dynamics in the induction of control mechanisms. β-Lg turned out to be more immunogenic and induced a more dominant Th1 response than κ-CN, which triggered a significantly higher IgE response. For both proteins, CD4+ lymphocyte profiles correlated with CD4+CD25+ and CD4+CD25+Foxp3+ T cells induction and interleukin 10 secretion, but β-lg induced more CD4+CD25+Foxp3- Tregs. Moreover, ex vivo studies showed the risk of interaction of immune responses to different milk proteins, which may exacerbate allergy, especially the one caused by β-lg. In conclusion, the applied model of in vivo and ex vivo exposure to β-lg and κ-CN showed significant differences in immunoreactivity of the tested proteins (κ-CN demonstrated stronger allergenic potential than β-lg), and may be useful for the estimation of allergenic potential of various food proteins, including those modified in technological processes.
Keyphrases
- immune response
- lymph node metastasis
- mouse model
- regulatory t cells
- high glucose
- machine learning
- oxidative stress
- toll like receptor
- diabetic rats
- dendritic cells
- squamous cell carcinoma
- transcription factor
- climate change
- inflammatory response
- drug induced
- endothelial cells
- big data
- peripheral blood
- artificial intelligence
- risk assessment
- electronic health record
- case control