Identification of Antimycobacterial from Actinobacteria (INACC A758) Secondary Metabolites using Metabolomics Data

Sains Malaysiana 51(5)(2022): 1465-1473 http://doi.org/10.17576/jsm-2022-5105-16

ABSTRACT Actinobacteria produce active secondary metabolite with medicinal properties, such as antibacterial or anticancer. However, there are some reports about the difficulties in discovering novel secondary metabolites. Therefore, the need for a new approach is obvious. Several factors such as types of nutrients in the culture media or different solvents used for extraction have been proven to influence the Actinobacteria secondary metabolite production. In this study, a combination of culture media optimization and metabolites fingerprint analysis were applied to identify antimycobacterial active compounds from Actinobacteria (InaCC A758). Five culture media were used in the secondary metabolite production of the Actinobacteria. The metabolite fingerprinting was carried out by analyzing the secondary metabolite profile extracted from culture media optimization using UPLC-MS. Multivariate analysis, i.e. cluster analysis and principal component analysis (PCA) was applied. The result showed that a unique antimycobacterial compound candidate against Mycobacterium smegmatis was produced by SYP media cultured InaCC A758 (MIC 6.25 µg/mL).

INTRODUCTION Actinobacteria is a phylum that occupies the largest taxonomy in the bacterial domain (Singh & Dubey 2018). Actinobacteria are Gram-positive bacteria with high G + C DNA, and have been proved to produce biologically active secondary metabolites with medicinal properties,  such as antibacterial or anticancer (Barka et al. 2016; Bérdy 2012; Lahlou 2013). Unfortunately, there was a decline in the number of novel secondary metabolite findings from Actinobacteria (Gaudêncio & Pereira 2015; Mammo & Endale 2015). Therefore, a new approach using optimization of culture parameters is needed to find a new secondary metabolites from Actinobacteria (Bode et al. 2002; Romano et al. 2018; Zhu et al. 2014;). Apart from the culture process, extraction can also affect the process of obtaining secondary metabolites with different levels of polarity (Sharma et al. 2011). During the extraction process, it should also be noted that secondary metabolites can be found not only in microbial cells (intracellular) but also can be released into the culture media (extracellular). Secondary metabolites produced in the optimization of culture and extraction process can differ in terms of biological activity, or the different classes of compounds (Rajan & Kannabiran 2014; Retnowati et al. 2018). Meanwhile, extracts produced from a culture of Actinobacteria are difficult to evaluate due to the diversity of its compounds. Methods of analyzing secondary metabolite profiles of Actinobacteria can be performed using tandem liquid chromatography (LC) separation techniques with mass detection using spectroscopy (MS). The LC-MS analysis method can be used to find the novel microbial secondary metabolites by matching LC-MS profile data with a natural product database (Hamedi et al. 2015; Zaher et al. 2015). If a natural product database is not available, multivariate statistical analyses such as Principal Component Analysis (PCA) or cluster analysis of LC-MS metabolite profile data can be used to predict novel secondary metabolites (Cordella 2012).

This research optimized the selection of culture media and solvents used for extraction in order to stimulate the unique and bioactive secondary metabolite production of Actinobacteria (InaCC A758). Antimycobacterial activity analysis of the extracts was conducted and combined with the results from the metabolite fingerprint analysis method, in order to determine the extract candidates with unique profiles to be explored further. The antimycobacterial activity was carried out by testing the secondary metabolite extract of InaCC A758 against Mycobacterium smegmatis, the Rapidly Growing Mycobacteria (RGM). Mycobacterium smegmatis usually nonpathogenic, but an increase in the number of people with immunodeficiency can increase the risk of infection. Rapidly growing mycobacteria are also difficult to eradicate because of their higher natural resistance to antimicrobial (BrownElliott et al. 2012; van Ingen et al. 2012).

Sains Malaysiana 51(5)(2022): 1465-1473 http://doi.org/10.17576/jsm-2022-5105-16