Metabolomic Profiling of Antiviral Scaevola Spinescens Extracts by High Resolution Tandem

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Metabolomic Profiling of Antiviral Scaevola Spinescens Extracts by High Resolution Tandem

Metabolomic profiling of antiviral Scaevola spinescens extracts by high resolution tandem mass spectroscopy.

Cock, IE1,2, Matthews, B3

Presenting author’s e-mail: [email protected]

1Biomolecular and Physical Sciences, Griffith University, Brisbane, Australia

2Environmental Futures Centre, Griffith University, Brisbane, Australia

3Smartwaters, Griffith University, Gold Coast, Australia

ABSTRACT

Non-targeted HPLC separation of crude extracts coupled to high resolution time-of- flight (TOF) mass spectroscopy is a powerful tool for the identification and characterisation of individual components in crude plant extracts. This technique allows for metabolite fingerprinting studies between extracts to compare their overall metabolic compositions and identify possible lead compounds. Scaevola spinescens is an endemic Australian plant with a history of therapeutic use by Australian Aborigines as an anti-infective and anti-cancer medicine. The medicinal bioactivities of this plant are poorly studied. S. spinescens extract antiviral activity was examined using an MS2 bacteriophage plaque reduction model system. Toxicity was determined using the Artemia franciscana nauplii bioassay. All extracts displayed antiviral activity in the MS2 plaque reduction assay with methanol, water, ethyl acetate, chloroform and hexane extracts inhibiting 95.2 ± 1.8 %, 72.3 ± 6.3 %, 82.6 ± 4.5 %, 100 ± 0 % and 47.7 ± 12.9 % of plaque formation respectively. All extracts were nontoxic in the A. fransiscana bioassay, indicating their potential as medicines for the control of RNA viruses. HPLC-MS/MS TOF analysis identified several hundred unique mass signals in the extracts. The molecular masses and putative empirical formulas are reported here, allowing for comparison between highly active and less active extracts. Furthermore, the putative identities of several compounds are reported. Through the generation of databases of the detected compounds, this metabolic profiling has allowed for rapid differentiation of compound profiles between active and less active extracts. This is expected to assist in the identification of the most important compounds for further separation and bioactivity studies.

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