Characterization of Aspergillus niger DNA by Surface-Enhanced Raman Spectroscopy (SERS) with Principal Component Analysis (PCA) and Partial Least Square Discriminant Analysis (PLS-DA) with Application for the Production of Cellulase

A new method based on surface-enhanced Raman spectroscopy (SERS) has been developed to monitor mutations in the DNA of Aspergillus niger to enhance the production of cellulase enzyme. The DNA of A. niger fungus was mutated at specific points by CRISPR-Cas9 and subsequently isolated prior to SERS analysis. Specific spectral features have been identified which are associated with the DNA bases where the mutations have taken place. Those mutations ultimately led to the enhancement of cellulase production. The SERS spectra have been differentiated by multivariate data analysis, including principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA). The results indicate that the changes at 567 cm(-1), 951 cm(-1), 1300 cm(-1), 1314 cm(-1), 1393 cm(-1), and 1442 cm(-1) are associated with DNA mutations. PCA is able differentiate mutated from unmutated A. niger DNA. Moreover, the PLS-DA model identified and discriminated samples with an accuracy of 100%. These findings open up new avenues to rapidly and accurately characterize industrially-relevant biological samples.