Skip to main content
European Commission logo print header

Bridging the world of fungi and dementia

Article Category

Article available in the following languages:

A new angle on the wrongly folded proteins of Alzheimer's

The black mould commonly found on fruit and veg have a striking similarity. They deal with the scourge of misfolded proteins in the same biochemical way and, as such, they were the subject of an EU study on Alzheimer's disease.

Health icon Health

The PROFITS (Bridging the world of fungi and dementia) project investigated the model fungus Aspergillus niger (A. niger) and its protein secretion, stress and failures. These were induced during forced expression of homologous and heterologous proteins as well as treatment with chemicals and activation of transcription factors through secretion stress responses. Project researchers collected and analysed 50 A. niger microarray samples from six independent experiments where failures in protein folding, intracellular transport and secretion had been induced. A total of 40 genes were identified that show condition-independent differential expression. Gene coexpression network analysis predicted gene content of known secretory pathways from the 14 000 genes of A. niger. Analysis supported the biological relevance of these modules, confirming coexpression network analysis as a valuable tool in future research. People suffering from Alzheimer's disease accumulate amyloid plaques and Tau proteins. Researchers applied stress using an antibiotic promoter system to express the fibrillogenic amyloid peptide Aß, its precursor protein and the intracellular tangle-forming Tau protein in A. niger. A. niger is fast-growing and easy to genetically manipulate. Analysis of disease related symptoms such as incorrect protein production can be achieved in a very short time and at minimal expense as compared with human cell models. This model could prove invaluable in drug discovery and testing.


Alzheimer's, misfolded proteins, Aspergillus niger, secretion, stress, gene coexpression network analysis

Discover other articles in the same domain of application