Antimicrobial activity of necklace orchids is phylogenetically clustered and can be predicted with a biological response method

Necklace orchids
(Coelogyninae, Epidendroideae) have been used in traditional medicine practices
for centuries. Previous studies on a subset of unrelated orchid species
utilized in these traditional practices revealed they possessed antimicrobial,
anti-inflammatory, and anti-oxidant activity, providing experimental proof for
their medicinal properties. To date however none of these species have been
investigated ethno-botanically in a phylogenetic context. This study thus
carried out comparative bioprospecting for a group of wild orchids using EBDCS
(the Economic Botany Data Collection Standards) organ targeted and biological
response methods. The traditional medicinal use of necklace orchids was
recorded from books and journals published between 1984 and 2016. Two orchids, Coelogyne cristata and Coelogyne fimbriata, were selected,
cultivated both indoors and outdoors, and the antimicrobial properties on
extracts from their leaves and pseudobulbs tested against a selection of human
pathogens. A molecular phylogeny of Coelogyninae based on nuclear ribosomal ITS
and plastid matK DNA sequences
obtained from 148 species was reconstructed with Maximum Likelihood (ML) using
RAxML, Maximum Parsimony (MP) using PAUP, and Bayesian Inference using MrBayes.
Bioprospecting comparison of EBDCS and biological response was carried out
using customized R scripts. Ethanolic extracts obtained from leaves of C. fimbriata inhibited growth of Bacillus cereus, Staphylococcus
aureus, and Yersinia
enterocolitica, confirming the antimicrobial properties of these extracts. Leaf extracts were
found to have slightly stronger antimicrobial properties for plants cultivated
outdoors than indoors. These differences were not found to be statistically
significant though.
Three hot nodes with high potency for antimicrobial activities were detected
with the EBDCS organ targeted classification method,
and eight hot nodes were detected with the biological response classification
method. The biological response classification method is thus a more effective
tool in finding hot nodes amongst clades of species with high medicinal
potential.