Poster Presentation Australian and New Zealand Metabolomics Conference 2018

Fourier Transform infrared spectroscopy fingerprint (FTIR) of Mycoparasitic Scytalidium parasiticum : differentiation in difference substrates by using Tri- Step infrared spectroscopy. (#103)

Rafidah Ahmad 1 , Choon Kiat Lim 2 , Nurul Fadhilah Marzuki 2 , Yit Kheng Goh 2 , Kamalrul Azlan Azizan 1 , You Keng Goh 2 , Kah Joo Goh 2 , Syarul Nataqain Baharum 1
  1. Institutes of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
  2. Advanced Agriecological Research Sdn Bhd, Petaling jaya, Selangor, Malaysia

Ganoderma boninense (G. boninsense) causes basal stem rot (BSR) remains the most devastating oil palm diseases with direct loss of the stand, reduced yield of diseased palms and shorter replanting cycle. A mycoparasite, Scytalidium parasiticum has been successfully isolated and showed that this mycoparasite could inhibit the growth of G.boninsense. We believed that the inhibition of G.boninsense is caused by the antagonist effects of metabolites that has been produced by this mycoparasite. Prior to the above hypothesis, the optimization of Scytalidium parasiticum growth medium was done on three different substrates (maize, rice and oil palm extract medium).  The study was conducted to compare the chemical profiles of S.parasiticum that grown in three different substrates which are maize, rice and oil palm extract media (OPEM). FTIR technique was used to screen the chemicals profiles as a preliminary study to understand the cellular composition of S.parasiticum that grown in different substrates. We have conducted the tri-step FTIR chemical profiles in combination of multivariate statistical analysis to compare the different FTIR spectra. From the PCA analysis and PLS-DA analysis of 1D-FTIR, chemical profiles of  S.parasiticum  grown in OPEM is well-distinguished from the other substrates group. The first two principal components (PC1 and PC2) described the variation in the X matrix (R2X=0.921) with an acceptable predictability of 89% (Q2X=0.888). The first component and the two components are accounting for 82% and 10% of total variation respectively. The predictive quality of the optimized PLS-DA model was low (Q2=0.21, with two components; R2x=0.917, R2Y=0.287). The first component and the two components are accounting for 82% and 9% of total variation respectively. The result obtained was further analyzed with Second Derivative Infrared (SD-IR) and Two- dimensional correlation infrared (2D-FTIR) to observe the differences of the infrared spectrum between S.parasiticum that grown specifically in OPEM. S.parasiticum that grown in OPEM showed distinct spectra from the other two substrates which belongs to protein, aldehydes, esters and ketones groups.