Quantification of rosmarinic acid from different plant species of lower Himalayan region and expression analysis of underlying L-Phenylalanine pathway.
Muhammad MugheesMuhammad Asad FarooqIhsan Ul HaqIftikhar ZebMuhammad AliZahoor HussainIrum ShahzadiMohammad Maroof ShahPublished in: Physiologia plantarum (2022)
This study adopts a very effective high-performance liquid chromatography (HPLC) technique for the quantitative determination of rosmarinic acid (RA) and PCR-based amplification of biosynthetic key regulators in Isodon rugosus, Daphne mucronata, and Viburnum grandiflorum from the lower Himalayan regions. Rosmarinic acid is engaged in a variety of biological processes and has significant industrial significance. In this study, it was identified from crude methanolic extract using thin-layer chromatography with a standard, and its content was quantified using HPLC without interrupting spikes using a mixture of methanol and deionized water containing acetonitrile (70:30 v/v) and acetic acid (0.1% v/v) at UV 310 nm absorption. We used RT-PCR to identify cDNAs encoding PAL, C4H, and RAS, and Image J's semi-quantitative analysis to quantify the expression levels of genes involved in RA production from chosen plant material. The highest levels of PAL, C4H, and RAS were detected, by band intensity, in the leaves and flowers of I. rugosus, which also exhibited a substantial quantity of RA. However, in V. grandiflorum and D. mucronata the transcript of the given genes was low. The concentration of RA ranged from 187.7 to 21.2 mg g -1 for I. rugosus, 17.42 to 5.42 mg g -1 for V. grandiflorum, and 15.19 mg g -1 for D. mucronata. This study demonstrated that the method for quantifying RA from a crude methanolic extract was effective, indicating that I. rugosus might be used as an indigenous alternative source of RA.
Keyphrases
- high performance liquid chromatography
- rheumatoid arthritis
- solid phase extraction
- mass spectrometry
- tandem mass spectrometry
- ms ms
- disease activity
- simultaneous determination
- ankylosing spondylitis
- poor prognosis
- oxidative stress
- deep learning
- wastewater treatment
- machine learning
- high resolution
- high speed
- genome wide
- anti inflammatory
- high intensity
- systemic sclerosis
- risk assessment