Inventory of Aspergillus niger Secretome
Author Information
Author(s): Braaksma Machtelt, Martens-Uzunova Elena S, Punt Peter J, Schaap Peter J
Primary Institution: TNO Quality of Life
Hypothesis
Can combining in silico predictions with shotgun proteomics improve the inventory of secreted proteins in Aspergillus niger?
Conclusion
The study improved the inventory of A. niger secretory proteins by combining gene-model predictions and experimental validation.
Supporting Evidence
- The study identified around 200 proteins with predicted signal peptides as secreted proteins.
- Concordant changes in the secretome were observed in response to different growth conditions.
- The expected accuracy of signal peptide prediction for proteins lacking homologous sequences is 85%.
- Experimental validation confirmed many of the in silico predictions.
Takeaway
Scientists figured out which proteins a fungus called Aspergillus niger can secrete by using computer predictions and lab tests.
Methodology
The study combined in silico predictions of signal peptides with shotgun proteomics to analyze the secretome of A. niger.
Limitations
The accuracy of predictions relies on the correctness of gene models, which can be inaccurate.
Digital Object Identifier (DOI)
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